U.S. patent application number 16/545038 was filed with the patent office on 2019-12-05 for database operations and data manipulation using search-on-the-fly.
This patent application is currently assigned to Vilox Technologies, LLC. The applicant listed for this patent is Vilox Technologies, LLC. Invention is credited to Joseph L. De Bellis.
Application Number | 20190370298 16/545038 |
Document ID | / |
Family ID | 68694067 |
Filed Date | 2019-12-05 |
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United States Patent
Application |
20190370298 |
Kind Code |
A1 |
De Bellis; Joseph L. |
December 5, 2019 |
Database Operations and Data Manipulation Using
Search-On-The-Fly
Abstract
A method for searching for data among a plurality of disparate
databases includes a processor: displaying an indication of
contents of each of the plurality of disparate databases,
comprising displaying a data field descriptor for one or more
database fields of each of the plurality of disparate databases;
receiving a search selection directed to one or more of the one or
more database fields; returning a first search result comprising
database entries matching the search selection; saving the first
search result as a first temporary database; receiving a second
search request directed to the first temporary database; returning
a second search result comprising entries in the temporary database
matching the further search request; and saving the second search
result as a second temporary database.
Inventors: |
De Bellis; Joseph L.;
(Southampton, NY) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Vilox Technologies, LLC |
Plano |
TX |
US |
|
|
Assignee: |
Vilox Technologies, LLC
Plano
TX
|
Family ID: |
68694067 |
Appl. No.: |
16/545038 |
Filed: |
August 20, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14214700 |
Mar 15, 2014 |
10402456 |
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16545038 |
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61852024 |
Mar 15, 2013 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/951 20190101;
G06F 3/00 20130101 |
International
Class: |
G06F 16/951 20060101
G06F016/951; G06F 3/00 20060101 G06F003/00 |
Claims
1. A method for searching for data among a plurality of disparate
databases, comprising: displaying an indication of contents of each
of the plurality of disparate databases, comprising displaying a
data field descriptor for one or more database fields of each of
the plurality of disparate databases; receiving a search selection
directed to one or more of the one or more database fields;
returning a first search result comprising database entries
matching the search selection; saving the first search result as a
first temporary database; receiving a second search request
directed to the first temporary database; returning a second search
result comprising entries in the temporary database matching the
further search request; and saving the second search result as a
second temporary database.
2. The method of claim 1, wherein the search result comprises
database entries from at least two disparate databases, the method
comprising: creating a merged search result by merging first search
results from a first disparate database with subsequent search
results from one or more additional disparate databases; and
displaying the merged search result as a third temporary
database.
3. The method of claim 1, wherein the first and second search
results comprise iconic representations of the database
entries.
4. The method of claim 1, further comprising displaying each of the
plurality of disparate databases and the temporary databases on the
user interface as a solid of revolution.
5. The method of claim 4, comprising displaying the database fields
on the user interface as facets of solids of revolution.
6. The method of claim 5, comprising: executing a Boolean OR search
operation by dragging a first solid of revolution over a second
solid of revolution; and executing a Boolean AND search operation
by dragging the second solid of revolution over the first solid of
revolution.
7. The method of claim 6, wherein the first and second solids of
revolution include at least one facet having a common data field
descriptor; wherein the first solid of revolution includes N facets
and the second solid of revolution includes M facets; and wherein
the Boolean OR operation produces a third solid of revolution
having ((N+M)-1) facets, the method comprising: combining the data
field entries of the facets having the common data field
descriptor, and displaying the third solid of revolution on the
user interface.
8. The method of claim 7, comprising displaying the third solid of
revolution with facets from the first solid of revolution in a
first color, facets from the second solid of revolution in a second
color, and combined facets in a third color.
9. The method of claim 6, wherein the first and second solids of
revolution include P facets having a common data field descriptor;
wherein the first solid of revolution includes N facets and the
second solid of revolution includes M facets; wherein P<N and
P<M; and wherein the Boolean AND operation produces a third
database list having P data fields, the method comprising:
selecting the P facets having the common data field descriptor, and
displaying the third database list on the user interface.
10. The method of claim 9, wherein P is greater than or equal to
four, the method comprising displaying the third database list as a
third solid of revolution.
11. The method of claim 6, further comprising: through the user
interface, receiving rotation commands from a user; rotating one or
more of the solids of revolution; and displaying rotated ones of
the solids of revolutions on the user interface.
12. The method of claim 4, comprising displaying the data fields as
lists in flat displays on the user interface.
13. The method of claim 12, comprising unfolding the solids of
revolution to generate the flat displays.
14. The method of claim 4, wherein each solid of revolution has
four or more facets.
15. The method of claim 4, comprising: displaying the first search
result as a first solid of revolution having N facets; and
displaying the second search result as a second solid of revolution
having N facets, wherein the second solid of revolution is smaller
than the first solid of revolution.
16. The method of claim 4, comprising: displaying the first search
result as a first solid of revolution having N facets; and
displaying the second search result as a second solid of revolution
having N facets, wherein the second solid of revolution is larger
than the first solid of revolution.
17. The method of claim 1, wherein the first search result
comprises a dynamic pull down list, and wherein the first search
result includes only those data fields for which at least one of
the disparate databases contains the search selection.
18. A non-transitory computer-readable storage medium containing
search-on-the-fly search and data manipulation instructions
searching for data among a plurality of disparate databases, the
instructions when executed by a processor, causing the processor
to: display an indication of contents of each of the plurality of
disparate databases, wherein the processor causes display of a data
field descriptor for one or more database fields of each of the
plurality of disparate databases; receive a search selection
directed to one or more of the one or more database fields; return
a first search result comprising database entries matching the
search selection; save the first search result as a first temporary
database; receive a second search request directed to the first
temporary database; return a second search result comprising
entries in the temporary database matching the further search
request; and save the second search result as a second temporary
database.
19. The computer-readable storage medium of claim 1, wherein the
search result comprises database entries from at least two
disparate databases, and wherein the processor: creates a merged
search result by merging first search results from a first
disparate database with subsequent search results from one or more
additional disparate databases; and displays the merged search
result as a third temporary database.
Description
RELATED APPLICATIONS
[0001] This patent application is a continuation of patent
application Ser. No. 14/214,700 filed Mar. 15, 2014 entitled
Database Operations and Data Manipulation Using Search-On-The-Fly,
which claims the benefit of provisional patent application Ser. No.
61/852,024 filed Mar. 15, 2013 entitled Database Operations and
Data Manipulation Using Search-On-The-Fly, which is a
continuation-in-part of U.S. patent application Ser. No. 11/979,255
entitled Search-On-The-Fly Search Engine, filed Oct. 31, 2007,
which is a continuation of U.S. patent application Ser. No.
10/871,050, filed Jun. 21, 2004 entitled
Search-On-The-Fly/Sort-On-The-Fly Search Engine, now U.S. Pat. No.
7,574,432, which is a division of U.S. patent application Ser. No.
09/513,340, filed Feb. 25, 2000, entitled
Search-On-The-Fly/Sort-On-The-Fly Search Engine for Searching
Databases, now U.S. Pat. No. 6,760,720. The disclosures of these
patent applications and patents are hereby incorporated by
reference in their entirety.
BACKGROUND
[0002] In the most general sense, a database is a collection of
data. Various architectures have been devised to organize data in a
computerized database. Typically, a computerized database includes
data stored in mass storage devices, such as tape drives, magnetic
hard disk drives and optical drives. Three main database
architectures are termed hierarchical, network and relational. A
hierarchical database assigns different data types to different
levels of the hierarchy. Links between data items on one level and
data items on a different level are simple and direct. However, a
single data item can appear multiple times in a hierarchical
database and this creates data redundancy. To eliminate data
redundancy, a network database stores data in nodes having direct
access to any other node in the database. There is no need to
duplicate data since all nodes are universally accessible. In a
relational database, the basic unit of data is a relation. A
relation corresponds to a table having rows, with each row called a
tuple, and columns, with each column called an attribute. From a
practical standpoint, rows represent records of related data and
columns identify individual data elements. The order in which the
rows and columns appear in a table has no significance. In a
relational database, one can add a new column to a table without
having to modify older applications that access other columns in
the table. Relational databases thus provide flexibility to
accommodate changing needs.
[0003] All databases require a consistent structure, termed a
schema, to organize and manage the information. In a relational
database, the schema is a collection of tables. Similarly, for each
table, there is generally one schema to which it belongs. Once the
schema is designed, a tool, known as a database management system
(DBMS), is used to build the database and to operate on data within
the database. The DBMS stores, retrieves and modifies data
associated with the database. Lastly, to the extent possible, the
DBMS protects data from corruption and unauthorized access.
[0004] A human user controls the DBMS by providing a sequence of
commands selected from a data sublanguage. The syntax of data
sublanguages varies widely. The American National Standards
Institute (ANSI) and the International Organization for
Standardization (ISO) have adopted Structured English Query
Language (SQL) as a standard data sublanguage for relational
databases. SQL comprises a data definition language (DDL), a data
manipulation language (DML), and a data control language (DCL). The
DDL allows users to define a database, to modify its structure and
to destroy it. The DML provides the tools to enter, modify and
extract data from the database. The DCL provides tools to protect
data from corruption and unauthorized access. Although SQL is
standardized, most implementations of the ANSI standard have subtle
differences. Nonetheless, the standardization of SQL has greatly
increased the utility of relational databases for many
applications.
[0005] Although access to relational databases is facilitated by
standard data sublanguages, users still must have detailed
knowledge of the schema to obtain needed information from a
database since one can design many different schemas to represent
the storage of a given collection of information. For example, in
an electronic commerce system, product information, such as product
SKU, product name, product description, price, and tax code, may be
stored in a single table within a relational database. In another
electronic commerce system, product SKU, product name, description,
and tax code may be stored in one table while product SKU and
product price are stored in a separate table. In this situation, a
SQL query designed to retrieve a product price from a database of
the first electronic commerce system is not useful for retrieving
the price for the same product in the other electronic system's
database because the differences in schemas require the use of
different SQL queries to retrieve product price. As a consequence,
developers of retail applications accessing product information
from relational databases may have to adapt their SQL queries to
each individual schema. This, in turn, prevents their applications
from being used in environments where there are a wide variety of
databases having different schemas, such as the World Wide Web.
[0006] A further problem with conventional searches, search
engines, data access and data retrieval is a tendency to return
very large amounts of data, or to require the search parameters to
be narrowed. When large amounts of data are presented, the display
may take many "pages" before all data is seen by the user. The time
and expense involved in such a data review may be significant,
inconvenient, not user friendly or efficient.
SUMMARY
[0007] Sort-on-the-Fly/Search-on-the-Fly data retrieval methods and
apparatus (hereafter, search-on-the-fly) provide an intuitive means
for accessing or searching databases, allowing a user to access or
obtain information about data in the database without having to
know anything about the database structure.
Sort-on-the-Fly/Search-on-the-Fly is an information gathering
process or analysis process about data stored in one or more
databases. The on-the-fly methods and apparatus often use or
include sorting and searching. While
Sort-on-the-Fly/Search-on-the-Fly may be a search engine or part of
a search engine, it may also stand alone or make calls to a search
engine. For example, database search engines may be used in
conjunction with on-the-fly methods and apparatus.
[0008] Using Sort-on-the-Fly/Search-on-the-Fly, a user selects a
desired term, and the user is delivered all instances of the
desired term, even if a specific file or table does not contain the
instance. For example, if a user wants to enter a database using
the name of a specific individual as a database entry point, a
database manager or other software will access the database using
the desired name, and will organize the results so that all entries
associated with that name are displayed. The database need not have
a specific file (in a flat database) or a table (in a relational
database) of names. The user may perform further on-the-fly
searches or information retrieval to narrow or focus the results,
or for other reasons. For example, given results for all names that
include the name "Smith," the user may then decide to obtain
information for all "Smiths" that include an association to an
address in New Jersey. Search-on-the-fly then conducts a further
information gathering using these criteria and produces a second
result. Further narrowing or broadening of the analysis is
permitted, with search-on-the-fly returning results based on any
new criteria.
[0009] In an embodiment, search-on-the-fly uses graphical user
interfaces (GUIs) and one or more icons to make the information
gathering process as efficient as possible. The GUIs may
incorporate one or more pull down menus of available sorting terms.
As a user selects an item from a first pulldown menu, a subsequent
pulldown menu displays choices that are available for sorting or
searching. The process may be continued or repeated until
Sort-on-the-Fly/Search-on-the-Fly has retrieved or displayed a
discrete data entry from the database. The pulldown menus are not
pre-formatted. Instead, the pulldown menus are created "on-the-fly"
as the user steps through the sort and/or search process. Thus,
search-on-the-fly is inherently intuitive, and allows a user with
little or no knowledge of the database contents, its organization,
or a search engine search routine to execute comprehensive
analysis, sorting and/or searches that return generally accurate
results.
[0010] A data search and manipulation method includes accessing, by
a processor, a first data element of a first data structure, the
first data structure represented by a first icon, the first icon
displayed in a user interface; accessing, by the processor, a
second data element of a second data structure, the second data
structure represented by a second icon displayed in the user
interface; executing, by the processor, a first data manipulation
process in response to the first icon dragged over the second icon;
and executing, by the processor, a second data manipulation process
in response to the second icon dragged over the first icon.
[0011] A method for searching data in a first database represented
by a first icon and a second database represented by a second icon
includes receiving a search request for a data element in the first
database; returning the data element; responding to a first
manipulation of the first and second icons, includes detecting a
first move of the first icon over the second icon, identifying the
first move as a first search request, the processor executing a
first search operation in response to the first search request, and
providing a first search result. The method further includes
responding to a second manipulation of the first and second icons,
including detecting a second move of the second icon over the first
icon, identifying the second move as a second search request, the
processor executing a second search operation in response to the
second search request, and providing a second search result
different from the first search result.
[0012] A system for searching and manipulating data, the data in a
first database represented by a first icon and a second database
represented by a second icon, includes a processor; and a
computer-readable storage medium containing search-on-the-fly
search and data manipulation instructions. The processor executes
the instructions to receive a search request for a data element in
the first database and return the data element. The processor
responds to a first manipulation of the first and second icons. The
processor detects a first move of the first icon over the second
icon, identifies the first move as a first search request, executes
a first search operation in response to the first search request,
and provides a first search result. The processor responds to a
second manipulation of the first and second icons. The processor
detects a second move of the second icon over the first icon,
identifies the second move as a second search request, executes a
second search operation in response to the second search request,
and provides a second search result different from the first search
result.
[0013] In an embodiment, a method for searching for data among a
plurality of disparate databases includes a processor: displaying
an indication of contents of each of the plurality of disparate
databases, comprising displaying a data field descriptor for one or
more database fields of each of the plurality of disparate
databases; receiving a search selection directed to one or more of
the one or more database fields; returning a first search result
comprising database entries matching the search selection; saving
the first search result as a first temporary database; receiving a
second search request directed to the first temporary database;
returning a second search result comprising entries in the
temporary database matching the further search request; and saving
the second search result as a second temporary database.
[0014] Search-on-the-fly also searches on key words specified by
the user. Search-on-the-fly can be used to exclude certain items.
Search-on-the-fly incorporates other advanced features such as
saving results by attaching a cookie to a user's computer, and
associating icons with the results.
[0015] Search-on-the-fly may be used with both internal and
external databases. For example, Search-on-the-fly may be used with
a company internal database and one or more databases accessible
through the Internet.
[0016] Search-on-the-fly is user-friendly. With one interface, many
different types of databases or database schemas may be searched or
sorted.
[0017] Finally, the search-on-the-fly technique, and other
techniques discussed above may be used in conjunction with a method
of doing business, particularly a business method that uses the
Internet as a communications backbone.
DESCRIPTION OF THE DRAWINGS
[0018] The detailed description will refer to the following
figures, in which like numerals refer to like objects, and in
which:
[0019] FIG. 1 is a block diagram of a system that uses a
search-on-the-fly/sort-on-the-fly process;
[0020] FIG. 2 is another overall block diagram of the system of
FIG. 1;
[0021] FIG. 3 is a detailed block diagram of the search engine used
with the system of FIG. 2;
[0022] FIG. 4 is an example of a search-on-the-fly using the search
engine of FIG. 3;
[0023] FIGS. 5-9 are detailed block diagrams of components of the
search engine of FIG. 3;
[0024] FIG. 10 is another example of a search-on-the-fly using the
search engine of FIG. 3;
[0025] FIGS. 11-15b are additional examples of a search-on-the-fly
using the search engine of FIG. 3;
[0026] FIGS. 16-20 are flow charts illustrating operations of the
search engine of FIG. 3;
[0027] FIG. 21 illustrates a further function of the search engine
of FIG. 3 in which results of more than one search are
combined;
[0028] FIGS. 22A-26 illustrate graphical user interfaces that may
be displayed in conjunction with operation of the system of FIG.
1;
[0029] FIGS. 27-31 illustrate additional features of search-on-the
fly searching.
DETAILED DESCRIPTION
[0030] Ordinary search engines place constraints on any search. In
particular, a partial ordering of available search criteria limits
application of the search engine only to certain search sequences.
The user is given a choice of search sequences, and the order in
which individual search steps in the search sequence become
available limits the direction of the search. A user who desires to
take a vacation cruise may use an Internet search engine to find a
desired vacation package. The search begins with presentation of a
list of general categories, and the user clicks on "travel," which
produces a list of subcategories. The user then clicks on "cruises"
from the resulting list of subcategories, and so on in a cumulative
narrowing of possibilities until the user finds the desired
destination, date, cruise line, and price. The order in which
choices become available amounts to a predefined "search tree," and
the unspoken assumption of the search engine designer is that the
needs and thought processes of any user will naturally conform to
this predefined search tree.
[0031] To an extent, predefined constraints are helpful in that
predefined constraints allow a search engine to logically and
impersonally order the user's thoughts in such a way that if the
user has a clear idea of what object the user wants, and if the
object is there to be found, then the user is assured of finding
the object. Indeed, the user may want to know that choosing any
available category in a search sequence will produce an exhaustive
and disjunctive list of subcategories from which another choice can
be made. Unfortunately, an unnecessarily high cost is too often
paid for this knowledge: The user is unnecessarily locked into a
limited set of choice sequences, and without sufficient prior
knowledge of the object being sought, this limitation can become a
hindrance. Specifically, where prescribed search constraints are
incompatible with the associative relationships in the user's mind,
a conflict can arise between the thought processes of the user and
the function of the search engine.
[0032] At one time, such conflicts were written off to the
unavoidable differences between computers and the human mind.
However, some "differences" are neither unavoidable nor
problematic. In the case of search engine design, the solution is
elegant: upon selecting a category or entering a keyword, the user
can be given not only a list of subcategories, but the option to
apply previously available categories as well. In slightly more
technical terms, the open topology of the search tree can be
arbitrarily closed by permitting search sequences to loop and
converge. Previous lists can be accessed and used as points of
divergence from which new sub-sequences branch off, and the
attributes corresponding to distinct sub-sequences can later be
merged.
[0033] Sort-on-the-fly/search-on-the-fly data analysis, sorting
access and retrieval methods and apparatus (hereafter,
search-on-the-fly search engine) provide an intuitive means for
analyzing various types of databases, allowing a user to obtain
information about and/or access data in the database without having
to know anything about the database structure. A user selects a
desired term, and a database manager reviews the database for all
instances of the desired term, even if a specific file or table
does not contain the instance. For example, if a user wants to
analyze the database using the name of a specific individual as a
database entry point, the database manager will search the database
or index using the desired name, and will organize the results so
that all entries associated with that name are displayed. The
database need not have a specific file (in a flat database) or a
table (in a relational database) of names. The user may perform
further on-the-fly searches to narrow the search results, or for
other reasons. The search engine then conducts a further search
using these criteria and produces a second search result. Further
narrowing or broadening of the search are permitted, with the
search engine returning results based on any new criteria.
[0034] This on-the-fly method or process can be used to simply
analyze data or gather information about data stored in a database.
The actual data itself does not need to be fetched, displayed,
printed or even sorted. The user may simply wish to use this tool
to "clean-up" data or understand how data could be sorted or for
other reasons.
[0035] FIG. 1 is a block diagram of a system 10 that uses
search-on-the-fly. In FIG. 1, a database 12 is accessed using a
hardware/software interface device 100 to provide data to a user
terminal 14. Additional databases 13 and 15 may also be accessed by
the terminal 14 using the device 100. The databases 12, 13 and 15
may use different schemas, or may use a same schema. As will be
described later, the device 100 may include the search-on-the-fly
search apparatus. In an alternative embodiment, the
search-on-the-fly search engine may be co-located with the terminal
14. In yet another embodiment, the search-on-the-fly search engine
may be incorporated into the structure of one or more of the
databases 12, 13 and 15. The device 100 may interface with any one
or more of the databases 12, 13 and 15 using a network connection
such as through the Internet, for example. Other communications
mediums may also be used between the terminal 14, the device 100
and any one or more of the databases 12, 13 and 15. These mediums
may include the public switched telephone network (PSTN), cable
television delivery networks, Integrated Services Digital Networks
(ISDN), digital subscriber lines (DSL), wireless means, including
microwave and radio communications networks, satellite distribution
networks, and any other medium capable of carrying digital
data.
[0036] The system shown in FIG. 1 is but one of many possible
variations. The search-on-the-fly search engine could also be
incorporated within a single computer, such as a personal computer,
a computer network with a host server and one or more user
stations, an intranet, and an Internet-based system, as shown in
FIG. 2. Referring again to FIG. 2, the terminal 14 may be any
device capable of displaying digital data including handheld
devices, cellular phones, geosynchronous positioning satellite
(GPS) devices, wrist-worn devices, interactive phone devices,
household appliances, televisions, television set top boxes,
handheld computers, and other computers.
[0037] FIG. 3 is a detailed block diagram of an exemplary
search-on-the-fly search engine 125. The search engine 125 includes
a request analyzer 130 that receives search requests 114 from the
terminal 14 (not shown in FIG. 3) and sends out updated requests
115 to a query generator 150. A status control 140 receives a
status update signal 116 and a request status control signal 118
and sends out a request status response 119 to the request analyzer
130. The status control 140 also keeps track of search cycles, that
is, the number of search iterations performed. The query generator
150 receives the updated requests 115 from the request analyzer 130
and sends a database access signal 151 to a database driver 170.
The query generator 150 receives results 153 of a search of the
database 12 (not shown in FIG. 3) from the database driver 170. The
query generator 150 provides a display signal 175 to the terminal
14. The database driver 170 sends a database access signal 171 to
the database 12. Finally, a database qualifier 160 receives
information 161 from the database driver 170 and provides a list
163 of available data fields from the database 12. As will be
described later, the list of available data fields 163 may be
displayed to a user at the terminal 14, and may be sorted and
processed using the request analyzer 130 in conjunction with the
database qualifier 160. The database qualifier 160 also receives
search information and other commands 131 from the request analyzer
130.
[0038] The search engine 125 may identify a database schema by
simply using a trial and error process. Alternatively, the search
engine 125 may use other techniques know in the art. Such
techniques are described, for example, in U.S. Pat. No. 5,522,066,
"Interface for Accessing Multiple Records Stored in Different File
System Formats," and U.S. Pat. No. 5,974,407, "Method and Apparatus
for Implementing a Hierarchical Database Management System (HDBMS)
Using a Relational Database Management System (RDBMS) and the
Implementing Apparatus," the disclosures of which is hereby
incorporated by reference.
[0039] The search engine 125 provides search-on-the-fly search
capabilities and more conventional search capabilities. In either
case, the search engine 125 may perform a preliminary database
access function to determine if the user has access to the database
12. The search engine 125 also determines the database schema to
decide if the schema is compatible with the user's data processing
system. If the database schema is not compatible with the user's
processing system, the search engine 125 may attempt to perform
necessary translations so that the user at the terminal 14 may
access and view data in the database 12. Alternatively, the search
engine 125 may provide a prompt for the user indicating
incompatibility between the terminal 14 and a selected
database.
[0040] The search engine 125 may conduct a search using one or more
search cycles. A search cycle includes receipt of a request 114,
any necessary formatting of the request 114, and any necessary
truncation steps. The search cycle ends when a result list 175 is
provided to the terminal 14. The search engine 125 may retain a
status of each past and current search cycle so that the user can
modify the search at a later time. The user may also use this
feature of retaining a status of past and current search cycles to
combine results of multiple searches, using, for example, a Boolean
AND function, a Boolean OR function, or other logic function. The
above listed functions will be described in more detail later.
[0041] The search-on-the-fly function of the search engine 125
begins by determining available data fields of the database 12. The
database 12 may have its data organized in one or more data fields,
tables, or other structures, and each such data field may be
identified by a data field descriptor. In many cases, the data
field descriptor includes enough text for the user at the terminal
14 to determine the general contents of the data field. The list of
data fields may then be presented at the terminal 14, for example,
in a pull down list. An example of such a data field result list is
shown in FIG. 4, which is from a federal database showing data
related to managed health care organizations. This database is
available at http://tobaccopapers.org/dnld.htm. In FIG. 4, the
first data field listed is "PlanType," which is shown in result
list 156. Other data field descriptors show the general categories
of data in the database.
[0042] Using the terminal 14, the user may select one of the data
field descriptors to be searched. For example, the user could
select "city." If a number of entries, or records, in the city data
field is short, a further result list of complete city names may be
displayed. If the entries are too numerous to be displayed within a
standard screen size, for example, the search engine 125 may, in an
iterative fashion, attempt to reduce, or truncate, the result list
until the result list may be displayed. In the example shown in
FIG. 4, entries in the city data field are so numerous (the
database includes all U.S. cities that have a managed health care
organization) that the search engine 125 has produced a result list
157 that shows only a first letter of the city. Based on the
available database data fields, the user may then perform a further
search-on-the-fly. In this case, the user may choose cities whose
first initial is "N." The search engine 125 then returns a result
list 158 of cities whose names start with the letter "N." Because
in this instance the result list 158 is short, no further
truncation is necessary to produce a manageable list.
[0043] FIG. 5 is a more detailed block diagram of the request
analyzer 130. A protocol analyzer 133 receives the request 114 and
provides an output 135 to a constraint collator 136. The protocol
analyzer 133 examines the received request 114, determines a format
of the request 114, and performs any necessary translations to make
the request format compatible with the database to be accessed. If
the database to be accessed by the terminal 14 is part of a same
computer system as the terminal 14, then the protocol analyzer 133
may not be required to perform any translations or to reformat the
request 114. If the database to be accessed is not part of the same
computer system as the terminal 14, then the protocol analyzer 133
may be required to reformat the request 114. The reformatting may
be needed, for example, when a request 114 is transmitted over a
network, such as the Internet, to a database coupled to the
network.
[0044] The constraint collator 136 provides the updated request 115
(which may be an initial request, or a subsequent request) to the
query generator 150. The constraint collator 136 is responsible for
interpreting the request 114. The constraint collator 136 performs
this function by comparing the request 114 against information
stored in the status control 140. In particular, the constraint
collator 136 sends the request status control signal 118 to the
status control 140 and receives the request status response 119.
The constraint collator 136 then compares the request status
response 119 to constraint information provided with the request
114 to determine if the constraint status should be updated (e.g.,
because the request 114 includes a new constraint). In an
embodiment, the constraint collator 136 compares constraint
information in a current request 114 to constraint information
residing in the status control 140, and if the current request 114
includes a new constraint, such as a new narrowing request (for
example, when the user clicks, touches or points over a field shown
in a last search cycle), then the constraint collator 136 adds the
updated information and sends the updated request 115 to the query
generator 150. If the constraint status should be updated, the
constraint collator 136 sends the status update 118 to the status
control 140. If the request 114 is a refresh request, the
constraint collator 136 sends a reset command 131 to the database
qualifier 160. The updated request 115 (possibly with a new
constraint) is then sent to the query analyzer 150 for further
processing.
[0045] FIG. 6 is a block diagram of the query generator 150. The
overall functions of the query generator 150 are to scan a
database, such as the database 12, using the database driver 170,
and to collect search results based on constraints supplied by the
request analyzer 130. The query generator 150 then returns the
search results 175 to the terminal 14.
[0046] The query generator 150 includes a truncator 152 and a
dispatcher 154. The truncator 152 receives the updated request 115,
including a new constraint, if applicable. The truncator 152
creates new queries, based on new constraints, and applies the new
requests 151 to the database 12 using the database driver 170. Many
different methods of truncating for display or viewing may be used
by truncator 152. The truncator 152 may include a variable limit
155 that is set, for example, according to a capacity of the
terminal 14 to display the search results 175. If data retrieved
from the database 12 exceed the limit value, the truncator 152
adjusts a size (e.g., a number of entries or records) of the data
until a displayable result list is achieved. One method of
adjusting the size is by cycling (looping). Other methods may also
be used to adjust the size of the result list. For example, the
terminal 14 may be limited to displaying 20 lines of data (entries,
records) from the database 12. The truncator 152 will cycle until
the displayed result list is at most 20 lines. In an embodiment,
the truncation process used by the truncator 152 assumes that if
the user requests all values in a particular data field from the
database 12, and there are no other constraints provided with the
request 114, and if the size of the resulting result list is larger
than some numeric parameter related to a display size of the
terminal 14, then the constraints may be modified by the truncator
152 so that the result list can accommodated (e.g., displayed on
one page) by the terminal 14. For example, instead of a full name
of a city, some part of the name--the first n letters--is checked
against the database 12 again, and n is reduced until the result
list is small enough for the capacity of the terminal 14. If the
maximum number of displayable results is three (3), and the
database 12 contains the names of six cities "Armandia, Armonk, New
Orleans, New York, Riverhead, Riverdale," then the first attempt to
"resolve" the result list will stop after a result list display is
created with the full name of the cities: Armandia, Armonk, New
Orleans . . . (the limit was reached) Try again with 7 characters:
Armandia, Armonk, New Orl, New Yor, (limit reached again) Again
with 5 characters: Armandia, Armonk, New O, New Y, (limit reached
again) Again with 3 characters: Arm ( . . . ), New ( . . . ), Riv (
. . . ). These results may now be displayed on the terminal 14. The
display of Arm, New, Riv can then be used to conduct a further
search-on-the-fly. For example, a user could then select Riv for a
further search-on-the-fly. The result list returned would then list
two cities, namely Riverhead and Riverdale.
[0047] In another embodiment, a fixed format is imposed such that
all queries generated against a database will have preset limits
corresponding to the capacity of the terminal 14.
[0048] In yet another embodiment, the truncator 152 may adjust the
field size by division or other means. For example, if the display
limit has been reached, the truncator 125 may reduce the field
size, X by a specified amount. In an embodiment, X may be divided
by two. Alternatively, X may be multiplied by a number less than 1,
such as 3/4, for example. Adjusting the field size allows the
search engine 125 to perform more focused searches and provides
more accurate search results.
[0049] In another embodiment, the truncator first attempts to
display information without truncation. If that is not appropriate,
the truncator may attempt truncation by beginning with one
character (26 letters and perhaps 10 digits) and incrementing to
two characters and then three, four, until a failure to display is
reached.
[0050] In still another embodiment, the user may select a limit
that will cause the truncator 152 to adjust the field size. For
example, the user could specify that a maximum of ten entries
should be displayed.
[0051] For certain data fields, a terminal of a hand-held device,
may have a very limited display capacity. For example, a personal
data assistant (POA--see FIG. 52) or a cellular phone (see FIG. 50)
may be used to search a database, with the results displayed on a
small screen. Alternatively, a user may specify a limit on the
number of entries for display. In the illustrated cases, the search
engine 125 may return a result list 175 of the request 114 on
multiple display pages, and the user may toggle between these
multiple display pages. As an example, if the terminal 14 is
limited to displaying a maximum of ten entries, and if the request
114 results in a return of a data field comprising the 400 largest
cities in the United States, the truncator 152 will produce a list
of 23 entries comprising 23 alphabetical characters (no cities that
begin with Q, Y or Z--see FIG. 4). The search engine 125 may then
display the results on three pages. Alternatively, the truncator
152 could produce a list of letter groups into which the cities
would fall, such as A-D, E-G, H-M, N-R, and R-X, for example. In
another alternative, the search engine 125 may send a notice to the
terminal that the request 114 cannot be accommodated on the
terminal 14 and may prompt the user to add an additional constraint
to the request 114, so that a search result may be displayed at the
terminal 14.
[0052] Adjusting the data field size also provides more convenient
search results for the user. For example, if a user were to access
an Internet-based database for books for sale, and were to request
a list of all book titles beginning with the letter "F," a common
search engine might return several hundred titles or more,
displaying perhaps twenty titles (entries) at a time. The user
would then have to look through each of many pages to find a
desired title. This process could be very time-consuming and
expensive. Furthermore, if the search results were too large, the
common search engine might return a notice saying the results were
too large for display and might prompt the user to select an
alternative search request. However, performing the same search
using the search engine 125 allows the truncator 152 to reduce the
size of the information displayed to a manageable level. In this
example, if the request 114 includes the constraint "F," the
truncator 152 will loop through the data in a data field that
includes book titles starting with the letter "F" until a list is
available that can fit within the display limits of the terminal
14, or that fits within a limit set by the user, for example. The
first list returned to the terminal 14 as a result of this request
114 may be a two-letter combination with "F" as the first letter
and a second letter of a book title as the second letter. For
example, the first list may include the entries "Fa," "Fe," "Fi,"
"Fo," and "Fu," all of which represent titles of books. The user
could then select one of the entries "Fa," "Fe," "Fi," "Fo," and
"Fu" to perform a further search, continuing the process until one
or more desired titles are displayed. An example of a similar
truncation result is shown in FIG. 14.
[0053] When a parameter related to the search results is adequately
truncated, the parameter is directed to the dispatcher 154, which
retrieves the data from database 12 using the database driver 170.
The dispatcher 154 then directs the final, truncated search results
175 back to the terminal 14 as a response to the request 114.
[0054] FIG. 7 is a block diagram showing the status control 140,
which is responsible for monitoring the status of a current search.
Due to the nature of the search engine 125, the user can choose any
combination of constraints, fields or keywords, including those
from past and current search cycles. The status control 140 may
keep track of all past cycles of the search, as well as all
information necessary to return to any of those past search cycles.
The status control 140 includes a status data module 142, and an
index module 144. The status data module 142 contains data related
to each such search cycle, including the constraint(s) entered
during the search cycle, any truncation steps taken, and the
results of such truncation, for example. The index module 144
provides access to these data. When the request 114 is being
analyzed by the request analyzer 130, the constraint collator 136
sends a request status query 116 to the index module 144. The
status data module 142 contains information related to all past and
current search cycles, which are referenced by the index module
144, and delivers a status response 119 for the most recent search
cycle to the constraint collator 136. When a new constraint is sent
to the query generator 150, the status data module 142 is updated
118 by the constraint collator 136. Specific structures of the
request 114, the request status query 116, the status response 119
and the request status control 118 will be provided later.
[0055] The status data module 142 may be reset by the database
qualifier 160 with all available fields when a refresh function is
used. In an embodiment, the refresh function may be used to clear
all past search cycles and the current search cycle from the status
control 140. In such an event, the search results, such as the
search results shown in FIG. 4, will no longer be displayed at the
terminal 14, and data related to the past and the current search
cycles may not be used for future search cycles. In effect, the
refresh function may cause the entire search to be discarded. The
refresh function may be activated when a user selects a refresh
button (see FIG. 4) on a displayed result list, or on another
portion of a GUI. Alternatively, the refresh function may discard
selected search cycles. In this alternative embodiment, the user
may, for example, move a cursor to a desired result list from a
past search cycle and activate a refresh, reset, back, or drop
button. All data associated with search cycles subsequent to the
selected search cycle, including all displayed result lists may
then be discarded.
[0056] FIG. 8 is a block diagram showing the database qualifier
160. The database qualifier 160 provides data field information at
the start of a search or when the search engine 125 is refreshed. A
field assessor 162 access the database 12 using the database driver
170, and identifies and accesses discrete data fields and other
information in the database 12. A field converter 164 structures
the data field information into a usable (searchable/sortable)
structure and sends 163 the formatted data field information to the
status control 140. Techniques for identifying and accessing the
data fields, and for formatting the data field information are well
known in the art. Such techniques are described, for example, in
U.S. Pat. No. 5,222,066, Interface for Accessing Multiple Records
Stored in Different File System Formats, the disclosure of which is
hereby incorporated by reference.
[0057] FIG. 9 is a block diagram of the database driver 170. The
database driver 170 is the universal interface with the database
12, which can be a local or a remote database.
[0058] FIG. 10 is an example of a search-on-the-fly using the
search engine 125. In FIG. 10, a database 200 includes information
related to a number of individuals. The information in the database
200 may be presented at the terminal 14 using a series of screens
or menus 201-230. The user first accesses the database 200 and is
presented with a list 201 of the information or data fields
contained in the database 200. The result list 201 is generated by
the field assessor 162, and is provided for display at the terminal
14 by the query generator 150. As shown in FIG. 10, a user has
selected the data field "City" for display of information. However,
the number of "cities" listed in the database 200 is too large to
conveniently display at one time (i.e., on one page) at the
terminal 14. Accordingly, the truncator 152 will loop a required
number of times until an adequate display is available. In FIG. 10,
the menu 203 shows the results of the truncation with only the
first letter of a city name displayed.
[0059] Using the menu 203, the user has selected cities beginning
with the letter "A.". The results are shown in menu 205. Now, the
user elects to conduct another search-on-the-fly, by selecting the
"sort-on-the-fly" option 206. The query generator 150 displays all
the information fields available from the database 200, except for
the information field already displayed, namely "City." The results
are displayed in menu 207. The user then elects to further search
on the data field "State." The query generator 150 returns the
requested information as displayed in menu 209, listing five states
by their common two-letter abbreviation. The user then chooses New
York from the menu 209, and the query generator 150 returns a list
of cities in New York, menu 211.
[0060] Next, the user elects to conduct another search-on-the-fly,
option 212, and the query generator 150 returns only the remaining
data fields for display in menu 215. From the menu 215, the user
selects "Address" for the next data field to search, and the query
generator 150 returns a menu 217 showing only first letters of the
address. This signifies that the data field "Address" was too large
to be easily displayed on the terminal 14. The user then elects to
search on all addresses that begin with "C." The query generator
150 returns a list of addresses by displaying only street names,
menu 219.
[0061] The user then elects to conduct a further search-on-the-fly,
option 220, and the remaining two data fields, "Name" and "Phone"
are displayed as options in menu 221. The user selects name, and
the query generator returns a further breakdown of the data by last
name and by first name, menu 223. This process continues, with
further menus being used to select a last name and a first name
from the database 200. When the final selection is made,
information from the database 200 related to the individual is
displayed in window 230.
[0062] In the example shown in FIG. 10, the user could have
refreshed the search engine 125 at any time, and the search would
have recommenced at the beginning. Alternatively, the user could,
by simply selecting a prior menu, such as the menu 215, have
changed the course of the search. In this alternative, if the user
had gone back to the menu 215 and instead of selecting "Address"
selected "Phone," then the menus 217-229 would be removed from
display at the terminal 14, and the search would begin over from
the point of the menu 215.
[0063] FIGS. 11-15b illustrate exemplary searches of a remote
database, such as the database 13 shown in FIG. 1. The database in
the illustrated example is for an Internet website 232 that sells
books. The examples illustrated are based on a Barnes &
Noble.TM. website. In FIG. 11, the user has applied the search
engine 125 to the website 232 database, and the query generator 150
has returned a list 233 of data fields from which the user may
select to access data from the website 232 database. The list 233,
and other lists described below, may be displayed as overlays on
the website 232. In the example illustrated, the user selects
"Title" for the first search cycle. Because the list of titles is
too large to easily display at the terminal 14, the truncator 152
loops until an alphanumeric list 234 is created. The list 234 is
then returned to the terminal 14. For the next search cycle, the
user selects titles that begin with the letter "C." Again, the data
field contains too many entries to conveniently display at the
terminal 14, and the truncator 152 loops as appropriate until list
235 is created. The process continues with subsequent lists 236 and
237 being returned to the terminal 14.
[0064] FIGS. 12-15b illustrate alternate searches that may be
completed using the website 232 database.
[0065] For the search results shown in FIGS. 11-15b, the status
control 140 may iterate as follows:
[0066] Status Control Started . . . Key: Title1 Option: Title
Level: 1 Filter: Field: Title Key: A2 Option: A Level: 2 Filter:
SUBSTRING([Title],1,1)=`A` Field: Title Key: AA3 Option: AA Level:
3 Filter: SUBSTRING([Title],1,2)=`AA` AND
SUBSTRING([Title],1,1)=`A` Field: Title Key: F4 Option: F Level: 4
Filter: SUBSTRING([Title],1,1)=`F` Field: Title Key: Fa5 Option: Fa
Level: 5 Filter: SUBSTRING([Title],1,2)=`Fa` AND
SUBSTRING([Title],1,1)=`F` Field: Title Key: Favo6 Option: Favo
Level: 6 Filter: SUBSTRING([Title],1,4)=`Favo` AND
SUBSTRING([Title],1,2)=`Fa` AND SUBSTRING([Title],1,1)=`F` Field:
Title Key: C7 Option: C Level: 7 Filter: SUBSTRING([Title],1,1)=`C`
Field: Title Key: Ce8 Option: Ce Level: 8 Filter:
SUBSTRING([Title],1,2)=`Ce` AND SUBSTRING([Title],1,1)=`C` Field:
Title Key: Cells9 Option: Cells Level: 9 Filter:
SUBSTRING([Title],1,5)=`Cells` AND SUBSTRING([Title],1,2)=`Ce` AND
SUBSTRING([Title],1,1) `C` Field: Title Key: Cellula10 Option:
Cellula Level: 10 Filter: SUBSTRING([Title],1,7)=`Cellula` AND
SUBSTRING([Title],1,2)=`Ce` AND SUBSTRING([Title],1,1)=`C` Field:
Title Key: CC11 Option: CC Level: 11 Filter:
SUBSTRING([Title],1,2)=`CC` AND SUBSTRING([Title],1,1)=`C` Field:
Title
[0067] Status Control Terminated.
[0068] FIG. 15b shows the results for a search for a low-fat
cookbook using the search engine 125 as applied to a remote
database. In this example, the remote database is coupled to a
Barnes & Noble web page. The first query, and resulting message
strings, are illustrated by the following: Query Analyzer Message
Received: ACK Status Control: Refresh Dispatcher Message Sent:
Categories.about.-.about.Title.about.-.about.Author.about.-.about.ISBN.ab-
out.SubTitle.about.Format.about.Date Published.about.Stock
Status.about.Recommended
Age.about.Pages.about.Ratings.about.Price.about.Retail.about.Savings.abou-
-t.-.about.Publisher Query Analyzer Message Received:
CLK#0#1#Categories Status Control received an update: Key:
Categories1 Option: Categories Level: 1 Filter: Field: Categories
Query Generator Request is not cached, processing Generated Query:
SELECT DISTINCT [Categories] FROM Books ORDER BY [Categories]
Number of Matching Records: 2032 Generated Query: SELECT DISTINCT
SUBSTRING([Categories],1,82) FROM Books ORDER BY
SUBSTRING([Categories],1,82) Number of Matching Records: 2022
Generated Query: SELECT DISTINCT SUBSTRING([Categories],1,61) FROM
Books ORDER BY SUBSTRING([Categories],1,61) Number of Matching
Records: 1995 Generated Query: SELECT DISTINCT
SUBSTRING([Categories],1,45) FROM Books ORDER BY
SUBSTRING([Categories],1,45) Number of Matching Records: 1751
Generated Query: SELECT DISTINCT SUBSTRING([Categories],1,33) FROM
Books ORDER BY SUBSTRING([Categories],1,33) Number of Matching
Records: 1251 Generated Query: SELECT DISTINCT
SUBSTRING([Categories],1,24) FROM Books ORDER BY
SUBSTRING([Categories],1,24) Number of Matching Records: 799
Generated Query: SELECT DISTINCT SUBSTRING([Categories],1,18) FROM
Books ORDER BY SUBSTRING([Categories],1,18) Number of Matching
Records: 425 Generated Query: SELECT DISTINCT
SUBSTRING([Categories],1,13) FROM Books ORDER BY
SUBSTRING([Categories],1,13) Number of Matching Records: 319
Generated Query: SELECT DISTINCT SUBSTRING([Categories],1,9) FROM
Books ORDER BY SUBSTRING([Categories],1,9) Number of Matching
Records: 147 Generated Query: SELECT DISTINCT
SUBSTRING([Categories],1,8) FROM Books ORDER BY
SUBSTRING([Categories],1,8) Number of Matching Records: 111
Generated Query: SELECT DISTINCT SUBSTRING([Categories],1,7) FROM
Books ORDER BY SUBSTRING([Categories],1,7) Number of Matching
Records: 78 Generated Query: SELECT DISTINCT
SUBSTRING([Categories],1,6) FROM Books ORDER BY
SUBSTRING([Categories],1,6) Number of Matching Records: 44
Generated Query: SELECT DISTINCT SUBSTRING([Categories],1,5) FROM
Books ORDER BY SUBSTRING([Categories],1,5) Number of Matching
Records: 26 Truncator finished, took 15 seconds to make 13
iterations Caching this request . . . Dispatcher Message Sent:
Afric.about.Art,
.about.Bio.about.Busin.about.Compu.about.Cooki.about.Engin.about.Enter.ab-
-out.Ficti.about.Histo.about.Home.about.Horro.about.Kids!.about.Law:
.about.Medic.about.Mind.about.Nonfi.about.Paren.about.Poetr.about.Refer.--
about.Relig.about.Scien.about.Small.about.Sport.about.Trave.about.Write.ab-
-out. Query Analyzer Message Received: CLKCategories
[0069] In the example illustrated by FIG. 15b and the above-listed
message strings, an initial request would have returned 2032 book
titles for cook books. This number of entries may be too large.
Accordingly, the truncator 152, through 13 iterations, reduces the
entries in a result list to 26. The entries in the truncated result
list can then be easily reviewed by the user, and further searches
may be performed to identify a desired book. As can be seen in FIG.
15b, the user has selected "Categories" as a data field to search.
As is also shown in FIG. 15b, the search engine 125 may display
other information windows, such as book availability, ordering and
shipping information windows. With a simple drag-and-drop cursor
operation, for example, the user may then order and pay for the
desired book.
[0070] FIG. 16-20 are flow charts illustrating operations of the
search engine 125. FIG. 16 is a flowchart of an overall search
routine 250. The process starts in block 251. The request analyzer
130 receives the request 114, block 252. The request 114 may be
made using a hierarchical menu-based display or a graphical user
interface, with one or more layers. Using either the menu or the
GUI, the user may enter specific details by typing, selection of
iconic symbols or pre-formatted text, and by using well-known data
entry techniques, for example. The request 114 may also comprise a
simple text or voice query. Use of voice recognition may be
particularly useful in mobile environments, and to speed access to
the database 12. Use of voice recognition may include simple
commands, such as UP, DOWN, and SELECT, to select search terms from
a pre-formatted list that is presented to the user at the terminal
14. More sophisticated use of voice recognition may include
actually speaking letters or numbers, or full search terms, such as
speaking a key word for a key word search, for example.
[0071] The protocol analyzer 133 provides an output 135 to the
constraint collator 136, and the constraint collator 136 determines
the nature of the request, block 254. If the request 114 is a
refresh request (i.e., a command to initiate the refresh function),
the constraint collator 136 sends a reset command 131 to the
database qualifier 160. The updated request 115 (possibly with a
new constraint) is then sent to the query analyzer 150 for further
processing, including analyzing the database 12, retrieving field
descriptors, and formatting, block 256. The result of the data
field descriptor retrieval and formatting are shown as an available
data fields result list, block 258, and is returned to the terminal
14, block 260.
[0072] In block 254, if the request 114 is not a refresh request,
the constraint collator 136 provides the updated request 115 (which
may be an initial request, or a subsequent request) to the query
generator 150, block 264. The constraint collator 136 compares the
request 114 against information stored in the status control 140.
In particular, the constraint collator 136 sends the request status
control signal 118 to the status control 140 and receives the
request status response 119. The constraint collator 136 then
compares the request status response 119 to constraint information
provided with the request 114 to determine if the constraint status
should be updated (e.g., because the request 114 includes a new
constraint). If the constraint status should be updated, the
constraint collator 136 calls create new constraint subroutine 270,
and creates new constraints.
[0073] The create new constraints subroutine 270 is shown as a
flowchart in FIG. 17. The subroutine starts at 272. In block 274,
the constraint collator 136 determines if the request is for a
sort-on-the-fly operation. If sort-on-the-fly has been selected,
field assessor 162 prepares a new set of data fields, block 280.
The new set of data fields are then sent to the query generator
150, block 284, and the subroutine 270 ends, block 286.
[0074] In block 274, if sort-on-the-fly was not selected, the
request analyzer 130 may receive a key word constraint, block 276.
The query generator 150 will then generate an input window in which
the user may enter a desired key word, block 282. Alternatively,
the query generator 150 may prompt the user to enter a key word
using voice recognition techniques, or any other way of entering
data. The process then moves to block 284. In block 276, if a key
word search option was not selected, the constraint collator 136
enters the new constraint to the existing list of constraints,
block 278. The process then moves to block 284.
[0075] Returning to FIG. 16, the constraint collator 136 next
updates the status control 140, block 290. In block 292, using the
updated constraints, the query generator 150 generates a next query
of the database 12, block 292. The database driver 170 then
extracts the result list from the database 12, according to the
latest query, block 294. In block 296, the truncator 152 determines
if the result list may be displayed at the terminal 14. If the
result list cannot be displayed, the process moves to block 298,
and a truncation routine is executed. The process then returns to
block 294. If the result list in block 296 is small enough, the
result list is provided by the dispatcher 154 to the terminal 14,
block 258.
[0076] As noted above, the request analyzer 130 determines the
nature of the request, including any special commands. A special
command may include a command to conduct a search-on-the-fly.
Alternatively, the search engine 125 may adopt a search-on-the-fly
mechanism as a default value. The search engine 125 also may
incorporate other special search commands, such as a Boolean
search, for example.
[0077] FIGS. 18-20 are flowcharts illustrating alternate truncation
subroutines 298. In FIG. 18, the subroutine 298 adjusts a size of a
data field by decrementing a parameter TP related to entries in a
selected data field. For example, if the data field comprises a
list of U.S. cities by name, the parameter TP may be the number of
alphabetical characters in a name. The results of such a truncation
is shown in the example of FIG. 4. The subroutine 298 starts at
block 301. In block 303, the parameter TP is set to equal a size of
the data field being searched. The truncator 152 then determines
the list of records sized by the parameter TP, block 305. In block
307, the truncator 152 determines if the result list can be
displayed at the terminal 14. If the result list cannot be
displayed at the terminal 14, the truncator 152 decrements the
parameter TP, block 309. Processing then returns to block 305, and
the truncator 152 gets a reduced result list using the truncated
parameter TP. If the result list can be displayed at the terminal
14, the process moves to block 311 and the subroutine 298 ends.
[0078] FIG. 19 is a flowchart illustrating an alternate truncation
routine 298'. The process starts in block 313. In block 315, the
truncator 152 sets the parameter TP to a size of the data field
being searched. In block 317, the truncator 152 determines the list
of records sized by the parameter TP. In block 319, the truncator
152 determines if the result list can be displayed at the terminal
14. If the result list cannot be displayed, the truncator 152
adjusts the size of the data field by dividing the parameter TP by
a set amount, for example, by dividing the parameter TP by two,
block 321. Processing then returns to block 317, and repeats. If
the result list can be displayed at the terminal 14, the process
moves to block 323 and the subroutine 298' ends.
[0079] FIG. 20 shows yet another alternative truncation subroutine
298''. The process starts in block 325. In block 327, the truncator
152 sets the parameter TP to equal the size of the data field being
searched. In block 329, the truncator 152 determines the list of
records sized by the parameter TP. The truncator 152 then
determines if the result list can be displayed at the terminal 14,
block 331. If the result list cannot be displayed at the terminal
14, the truncator 152 determines if the parameter TP is less than
ten, block 333. If the parameter TP is not less than ten, the
truncator 152 adjusts the parameter TP by multiplying the parameter
TP by a number less than one, block 337. In an embodiment, the
number may be 3/4. The process then returns to block 329 and
repeats. In block 333, if the value of the parameter TP is less
than ten, the truncator 152 decrements the parameter TP by one,
block 335. Processing then returns to block 329 and repeats. In
block 331, if the list can be displayed at the terminal 14, the
process moves to block 339 and the subroutine 298'' ends.
[0080] The examples illustrated in FIGS. 18-20 are but a few
examples of the truncation subroutines. One of ordinary skill in
the art could conceive of other methods to adjust the field size.
In addition to using a truncation subroutine, the user may specify
a limit for the field size.
[0081] As noted above, the search engine 125 may be used for
multiple searches and may be used to search multiple databases,
including databases with different schemas. The results of
individual searches, including the control data provided in the
status control 140, are saved. The search engine 125 may then be
used to further sort (search), or otherwise operate on, the results
of these multiple searches. In an embodiment, the search engine 125
may perform a Boolean AND operation on two search results. The
result of the Boolean AND operation would be a list of records, or
entries, that are common to the two search results. FIG. 21
illustrates such a Boolean AND operation.
[0082] In FIG. 21, a GUI 400 displays local database selections
410, including a database of recordings (compact discs--CDs) 412
and a database of contacts 414. The databases 412 and 414 may be
shown by text descriptions and an appropriate icon, for example.
The database selections in this example are resident on a user's
terminal, such as the terminal 14 shown in FIG. 1. Also displayed
on the GUI 400 is a remote database selection 420 that represents
databases, such as the databases 13 and 15 shown in FIG. 1, that
are located remotely from the terminal 14. In the example shown in
FIG. 21, the remote database selection 420 includes a database 422
for online record sales, which is represented by an icon (a CD) and
a text title of the online retailer. The remote databases shown in
the remote database selection 420 may include those databases for
which the user has already established a link. In the example
shown, the user may already have entered an Internet address for
the online retailer. In addition to any returned web pages from the
online retailer, the terminal 14 may then display a representation
of the database 422.
[0083] Continuing with the example, the user may use the search
engine 125 to conduct a search-on-the-fly of the recordings
database 412 and the Virgin Records.TM. database 422. The user may
search both databases 412 and 422 for titles of recordings that are
classified as "blues." The search engine 125 may return search
results 416 and 424 for searches of both databases 412 and 422,
respectively. The search results 416 and 424 may be displayed in a
window section 430 of the GUI 400. The results 416 and 424 may also
be represented by CD icons, such as the icons 432 and 434. The
search results 416 and 424 may be stored as lists in one or more
temporary databases, as represented by the windows 417 and 427. The
search results 416 and 424 may also be stored in a scratch pad
database 418. At this point, the user may wish to determine which
recordings from the list 424 are contained in the list 416. The
search engine may support this function by performing a Boolean AND
operation of the lists 416 and 424. The results of the Boolean AND
operation are represented by the icon 436 displayed in the window
430. To execute the Boolean AND operation, the user may simply drag
the icon 432 over the icon 434, and then select AND from a pop-up
menu 438 that appears when the icons 432 and 434 intersect. Other
techniques to execute the Boolean AND (or another Boolean function)
may include typing in a command in a window, using voice
recognition techniques, and other methods. In addition, other
Boolean functions may be used.
[0084] The result represented by the icon 436 of the Boolean AND
operation may then be stored in a database at the terminal 14, such
as in the scratch pad database 418 or may be stored at another
location. The result may then be subjected to further
search-on-the-fly operations.
[0085] Also shown in FIG. 21 is an online-purchase module 435 that
may be used to consummate purchase of a product referenced in an
online database such as the database 422. To initiate such a
purchase, the user may drag an iconic or text representation of a
desired product listed in the search result 424 over an icon 436 in
the online-purchase module 435. This drag-and-drop overlaying these
icons may initiate and complete the online purchase for the desired
product.
[0086] Use of the search engine 125 may be facilitated by one or
more GUIs that are displayed on the terminal 14. FIGS. 22-26 are
examples of such GUIs. In FIG. 22, a GUI 450 includes a display
section 452 and one or more database sections such as local
database section 470 and remote database section 460. The local
database section 470 includes databases local to the terminal 14.
In the example shown, the local databases include a patients'
database 472, a general contacts database 474, a pharmacy database
476, a medicines database 478 and a scratch pad database 480. The
remote databases include an Amazon.com database 462, an online
record retailer database 464, a Physician's Desk Reference database
466 and an American Medical Association (AMA) online database 468.
The remote and local databases may be represented by a text title
and an icon, both contained in a small window as shown. A user may
access one of the remote or local databases by moving a cursor over
the desired window and then selecting the database. In the example
shown, the local medicines database 478 has been selected, and a
list 490 of data fields in the medicines database 478 is displayed
in the display section 452. Also included on the display section
452 is a keyword button 492 that may be used to initiate a key word
search of the medicines database 478.
[0087] FIG. 23 shows the GUI 450 with a user selection of a
category data field from the list 490. The category data field is
indicated as selected by an arrow adjacent to the data field name.
When the category data field is selected, a category list 494 is
displayed on display section 452. The category list 494 includes
four entries, as shown.
[0088] The user may continue to search the medicines database 478
using key word techniques and search-on-the-fly techniques. FIG. 24
shows the GUI 450 with results of several search cycles
displayed.
[0089] FIG. 25 illustrates a search of the PDR database 466. Such a
search may be initiated by dragging a cursor to the window having
the PDR 466 symbol (text or icon), and then operating a "select"
button. FIG. 26 shows a search of the Amazon database 462. This
search may also be initiated by a "drag-and-drop" operation.
[0090] The SOF search engine 125 may accommodate merging of one or
more sets of search results. The multiple search results may be
derived from a common database, or from more than one database. A
search using the search engine 125 may be controlled through a user
interface by one or more icons that can represent (1) filters or
(2) the images of filters. Thus, the icon may represent spatial or
temporal attributes, or sets of objects or procedures. Merging the
icons thus has two interpretations corresponding to (1) and (2):
either filters are added ("apply every filter in every icon to
every image to which it can be applied"), or image sets are added.
In an alternative embodiment, the addition (union or join) operator
may be any other relational operator, e.g. divide, difference.
[0091] In various aspects, the SOF search engine 125 provides many
unique and powerful database operations. These operations in data
manipulation that involves chirality; faceted search and facet
manipulation; including facet rotation, dynamic data functions,
including database content exposition involving, for example,
dynamic pull down menus, data rotation; taxonomy control,
variation, and biasing; database and database cleansing; data
visualization; data parsing, re-amalgamation, retagging, and
database repopulation; and diverse data mining operations. The SOF
search engine 125 provides an intuitive computer-human interface
that matches the unique parallel processing of the human brain and
the rapid serial processing of a digital computer. These aspects of
the SOF search engine 125 make possible many additional features
and information display and data manipulation products and
services, including data representation and manipulation through
icon combinational variance, not available with current database
management systems and concepts. These aspects of the SOF search
engine 125 are disclosed above, and are shown in FIGS. 22A-31 and
are explained in more detail below.
Chirality
[0092] The SOF SE 125 allows for chiral manipulation of data
objects. A human left hand has a chiral representation to a human
right hand. When closed, the left hand is a non-superposable mirror
image of the right hand; no matter how the two hands are oriented,
it is impossible for all the major features of both hands to
coincide. Chiral manipulation of data objects using SOF SE
technology may be understood with reference to FIGS. 22A-22C.
[0093] As noted above, GUI 450, shown for example in FIG. 22B,
includes a display section 452 and one or more database sections
such as local database section 470 and remote database section 460.
The local database section 470 includes databases local to the
terminal 14. In the example shown, the local databases include a
patients' database 472, a general contacts database 474, a pharmacy
database 476, a medicines database 478 and a scratch pad database
480. The remote databases include an Amazon.com database 462, an
online record retailer database 464, a Physician's Desk Reference
database 466 and an American Medical Association (AMA) online
database 468. The remote and local databases may be represented by
a text title and an icon, both contained in a small window as
shown. A user may access one of the remote or local databases by
moving a cursor over the desired window and then selecting the
database. In the example shown, the local medicines database 478
has been selected, and a list 490 of data fields in the medicines
database 478 is displayed in the display section 452. Also included
on the display section 452 is a keyword button 492 that may be used
to initiate a key word search of the medicines database 478. Thus,
the illustrated databases are represented in GUI 450 by a number of
different icons.
[0094] The icons of GUI 450 are data objects. Manipulation of the
icons illustrates the chiral nature of their data representation.
For example, the patients' database 472 is represented by an
address card file icon 472A. Pharmacy data base 476 is represented
by a pharmacy icon 476A. Medical database 478 is represented by
medical icon 478A. Dragging the patients' database icon 472A over
the pharmacy icon 476A (path A, FIG. 22B) instructs the SOF SE 125
to execute a first operation. Dragging the pharmacy icon 476A over
the patients' database icon 472A (i.e., path B, FIG. 22C) instructs
the SOF SE to execute a second operation. In this example, the
first operation (FIG. 22B) may be to produce a database listing
476B of all medicines currently prescribed (i.e., prescriptions) to
each of the patients in the database 472. The database listing 476B
may include full or partial patient information as provided in the
patients' database 472. The database listing 476B further may
include a full or partial listing of the prescriptions as contained
in the pharmacy database 476. The full or partial listing from the
pharmacy database 476 may include information such as prescription
date, expiration, refills, generics, and pharmacy information
including pharmacy contact information and pharmacist name. The SOF
SE 125 further may select icon 476C to represents the database
listing 476B. The database listing 476B and icon 476C may be stored
in a local data repository such as the virtual scratch pad database
480, and may be displayed on the GUI 450 as separate database 476B.
The icon 476C and its underlying database 476B may be used in
subsequent search-on-the-fly operations, such as sending a new
prescription for a particular patient to a pharmacy (after
appropriate medical examination and review by the prescribing
physician).
[0095] Referring to FIG. 22C, icon merge and database manipulation
process of path B involves dragging the pharmacy database icon 476A
patients' database icon 472A may send a prescription to a patient's
preferred or designated pharmacy. A physician, during the course of
a day's medical examinations, for example, may require several
prescriptions, which the physician may enter into the pharmacy
database 476. By dragging the pharmacy database icon 476A over the
patients database icon 472A, the physician may send an appropriate
prescription, in the form of a digitally-signed electronic document
resembling a hard copy prescription writ. This dragging operation
of path B also may send a prescription drop-off notification to the
patient using email, text, or voice messaging. The icon merge
operation may produce database listing 472B, which may take the
form of prescription information for the patient. The database
listing 472B may be accompanied by icon 472C, which may be in the
form of a prescription writ. The database listing 472B and icon
472C may be stored in the virtual scratch pad database 480, for
example.
[0096] As may be appreciated by reference to FIGS. 22A-22C, an icon
merge operation along path A produces different results from those
of an icon merge along path B, illustrating the chiral nature of
icon merge operations executable using search-on-the-fly
technology. This chirality may be a default condition established
with the construction of the underlying databases. In an
alternative, a user may establish chiral merge operations through
use of an appropriate GUI.
Faceted Search
[0097] Search-on-the-fly technology, as disclosed herein, permits a
rich-exposition of data from any database or merge of multiple
databases. In viewing a database, the database fields generally are
shown as a flat, two-dimensional structure; namely a page or sheet
of paper. However, using a SOF search engine 125, this ordinary
representation of data may be enhanced significantly to show all
the rich variation of data possible in a faceted search. Rather
than the "sheet of paper" view of data, the SOF search engine 125
may be used to present the data in one of a number of facets of a
solid object. Consider a database that has six dimensions.
Referring to FIG. 24, medicines database 478 may be seen to have
six dimensions, namely Category, Brand Name, Generic Name, Dosage,
Price, and Specifications. That is, using the SOF search engine
125, an iterative search of the database 478 may be conducted
starting with any of these six dimensions. FIG. 24 shows just such
a search. As a first dimension, Category, is selected,
sub-categories are revealed, namely Antibiotics, Antidepressants,
Narcotics, and Other. The iterative search results 494, 500, 506,
and 510 show the effect of applying the SOF search engine 125 to
the medicines database 478.
[0098] However, even more information is available using the power
of the SOF search engine 125. Consider now how the original six
dimensions would appear if expressed in a solid, or body of
revolution. For six dimensions, such a solid, with equal sized
facets, would be a cube. The SOF search engine 125 may render the
database 478 on the GUI 450 as a cube, with each dimension
occupying a facet of the cube. FIG. 27 shows such a rendering. The
SOF search engine enables rotation of the cube to allow a user to
view the contents of each facet or dimension of the cube 600.
[0099] Note that any facet of the cube may display further search
results when a search on any one dimension is conducted. Note also
that if the contents of any database would exceed the display
capacity of a facet, the results may be truncated. Thus, and
considering the search results shown in FIG. 11, for example, the
selection of Title for the next iteration of an iterative search
returns too may results to be entirely shown, as can be seen in
results field 234. Thus, the SOF search engine 125 may return a
truncated list of titles, and further iterative searches may result
in truncation until the results may be displayed in a facet without
truncation.
[0100] As an alternative, the SOF search engine 125, when
displaying search results in the graphical form of a faceted solid,
may resize the solid when the results of a search iteration produce
a smaller number of entries in a facet than existed before the
search. That is, the cube may shrink. Correspondingly, the cube may
expand when the number increases.
[0101] As another alternative, each iteration of the search may
produce a unique cube, smaller or larger in size than its
predecessor. Thus, a search with three iterations may produce three
cubes, each of which may be displayed in the GUI, and each of which
may differ in size from the others. See FIG. 28.
[0102] The SOF search engine 125, and associated search technology,
then, may be used to create any shape with any number of facets.
The solid (image) produced by this process takes on an appearance
similar to that of a soccer ball, with facets for panels of the
ball, when the number of database dimensions increases. Each such
facet, or panel of the solid is an entry point into the overall
database or data structure represented by the solid. The solid may
be manipulated by "reaching in" to a specific facet and "viewing
by" the data as shown, for example, in a flat view, by FIG. 24.
[0103] As is shown in FIG. 29, the GUI 450 includes a control
feature that allows manipulation of the cube(s). For example, a
user may hover a cursor (not shown) over a cube to select that
cube, and then by operation of slide bar 690, may rotate the cube
so that the selected facet is displayed in a plane of the GUI.
Thus, as shown, facet 601 of cube 600 is in the plane of the GUI
450.
[0104] Another powerful aspect of the SOF search engine 125 is the
ability to merge databases, data sets, data dimensions, and data in
an intuitive fashion that convey the rich power of
search-on-the-fly technology. Consider databases 476 and 478, shown
in FIG. 28. Database 476 has six dimensions, and as before, may be
represented by a cube 600. Database 478, however, has five
dimensions and may be represented as a pyramid. However, database
478 has two data dimensions that do not exist in the database 476,
namely health warning issued by the drugs' manufacturers, and shelf
life. A user may be interested in of merging the two databases 478
and 476. FIG. 27 shows the result of the merge, namely an
eight-sided solid 640. In addition, for overlapping entries in a
specific data dimension, the overlap may be indicted by one color,
such as blue, and the non-overlapping entries by two other colors,
such as green and red, to indicate the origin of the entries. As
before, the GUI 450 may incorporate control features that allow
"rotation" of the displayed solids.
[0105] In addition to the above-disclosed features, a solid such as
the eight-sided solid of FIG. 27 may be "unfolded" to produce a
more traditional view of the data--for example, FIG. 24. In
unfolding the solid, the order of steps in any iteration, if
represented in the solid, may be reflected in the unfolded
view.
[0106] In addition to the above-described control features, the GUI
450 may incorporate touch screen displays, and the solid may be
rotated along an infinite number of axes, much like spinning a
globe or rolling a ball.
Dynamic Pull Down Menu
[0107] The SOF search engine 125, as disclosed previously, produces
dynamic search results. Referring again to FIG. 24, a search of
medicines by category produces a list of three drugs, plus "Other."
This list is dynamic, and constitutes a dynamic pull-down menu for
further searching and selection. The list is dynamic in that the
SOF search engine 125 may return results only if the underlying
database contains an enumerated item. Thus, for example, if the
database 478 does not contain any antibiotics, the result list 494
would not have the entry "Antibiotics." This effect has significant
consequences. The absence of an entry means the database has no
instances of the data item. Thus, a user may, by simple inspection,
determine the entire breadth of coverage of a database by noting
what is shown in a search result field and what is not shown.
[0108] Note that this feature applies to all databases accessible
by the SOF search engine 125. In FIG. 24, the illustrated SOF
search is of the medicines database 478. However, the SOF search
engine 125 may be controlled to search any or all of the external
database shown in section 460, as well as those shown in section
470. The SOF search engine 125, in returning search results may
include data entries from all appropriate databases resident on, or
linked to terminal 14. For example, the SOF search engine 125, when
searching all databases for the term antibiotics, may search the
databases 476, 478, and 466, 468.
Parse/Amalgamate/Re-Label/Repopulate
[0109] The SOF search engine 125 permits powerful data parsing and
re-labeling, and database repopulation. Consider the data search
results shown in FIG. 30. Under results, Attorney (705), a number
of individual attorney names and firm names are listed (since the
truncated term "Dor" was selected in the prior iteration). The
Attorney results list 705 for "Dor," in effect, could be a
database, database dimension, or field. However, only names
beginning with Dor are shown. As a result, the name "HereII," which
appears as the second name in the second entry may not be
separately searchable. However, the entries in the Attorney field
705 may be parsed to separate out any definable data element. For
example, the firm names may be parsed according to each proper
name, first and second names appearing in the firm name, the
"&" symbol, the word "and," and if listed, the corporation type
(e.g., PLLC, PLC, etc.) The thus-parsed data elements could then be
amalgamated. Suppose a user were interested in the corporate
designation. The data may be parsed to break out this term, where
existing. The corporate designation then may be formed as a
separate data dimension and may be labeled as "law firm corporation
type." Then the database may be repopulated with this data element.
Subsequent searches of the database may include a search-on-the-fly
search for lay firm corporation type.
Data Cleansing
[0110] A powerful feature of search-on-the-fly searching is the
ability of the SOF search engine 125 to explicitly and clearly show
errors and inconsistencies in any database. Consider the search
results shown in FIG. 31 for the USPTO database with assignee name
as a search term. Iterative searching leads to results of "M" and
then "Minnesota Mining and Manufacturing Company." The returned
search results clearly show the inconsistent nature of entries for
this assignee. Of course, inconsistent entries may not result in
actual errors. However, if the assignee name were spelled with one
"n" in Minnesota, the entry would be outside the range of actual,
correct assignee names for 3M. But the graphical nature of SOF
search engine search results would place the erroneous result
within the same window as the correct results, and thus, the
erroneous result may be noticed by a user reviewing the search
results. Thus, the error may be detected.
[0111] Once detected, the user need only select the erroneous entry
and a correct entry, and with a single `cleanse" command, correct
the error--the SOF search engine 125 performs a merge of the two
data entries and replaces the erroneous entry with a correct
entry.
Virtual Scratch Pad
[0112] A virtual scratch pad allows a user to maintain data in a
convenient, easy to access, review, and manipulate area of the
terminal 14. Virtual scratch pad database 480 is illustrated, for
example, in FIG. 22A. The virtual scratch pad database may be an
amalgamation of databases, database search results, and similar
data. The virtual scratch pad data base 480 may contain data for a
limited time, or until deleted by a user. The virtual scratch pad
database 480 may include data searchable together by the SOF search
engine 125. For example, the virtual scratch pad database 480 may
include search results for several different searches of the PDR
database 466. Searching the virtual scratch pad database 480 may
mean searching on the fly, the search results as if the results
were amalgamated into a single list.
[0113] While using search on the fly has been described in detail
for an end result of printing, viewing or displaying data, search
on the fly can be useful for other purposes. Search on the fly does
not require obtaining the underlying data in the database or the
display of the underlying data to be useful. Search on the fly can
be used for gathering information or characteristics about data in
a database with or without downloading the data itself. This
gathered information about the data can be used to analyze the
data, sorting, correct or clean data, verifications and
confirmations. For example, search on the fly can be used to
determine whether there is existing data in a database within
certain ranges or parameters (date ranges, numerical,
alphanumerical and other characteristics). If there is data within
certain parameters, the number of datapoints within those
parameters can also be determined. This information about the data
can be gathered using search on the fly with queries to the
database manager (which may simply need to query its index and not
access the data itself). Another example is correcting data. Data
may need to be corrected or cleaned for various reasons including
spelling errors. Search on the fly can locate these errors without
necessarily accessing and downloading the data itself. Certain
combinations of characters or truncations will be obvious spelling
errors. Also, data that is out of range can be located and
corrected or eliminated from the database using search on the fly.
Another example is data from one database can be confirmed or
verified against data in a second database using search on the fly.
Those skilled in the art will find many uses and specific
applications for search on the fly.
[0114] Certain of the devices shown in the herein described figures
include a computing system. The computing system includes a
processor (CPU) and a system bus that couples various system
components including a system memory such as read only memory (ROM)
and random access memory (RAM), to the processor. Other system
memory may be available for use as well. The computing system may
include more than one processor or a group or cluster of computing
system networked together to provide greater processing
capability.
[0115] The system bus may be any of several types of bus structures
including a memory bus or memory controller, a peripheral bus, and
a local bus using any of a variety of bus architectures. A basic
input/output (BIOS) stored in the ROM or the like, may provide
basic routines that help to transfer information between elements
within the computing system, such as during start-up. The computing
system further includes data stores, which maintain a database
according to known database management systems. The data stores may
be embodied in many forms, such as a hard disk drive, a magnetic
disk drive, an optical disk drive, tape drive, or another type of
computer readable media which can store data that are accessible by
the processor, such as magnetic cassettes, flash memory cards,
digital versatile disks, cartridges, random access memories (RAM)
and, read only memory (ROM). The data stores may be connected to
the system bus by a drive interface. The data stores provide
nonvolatile storage of computer readable instructions, data
structures, program modules and other data for the computing
system.
[0116] To enable human (and in some instances, machine) user
interaction, the computing system may include an input device, such
as a microphone for speech and audio, a touch sensitive screen for
gesture or graphical input, keyboard, mouse, motion input, and so
forth. An output device can include one or more of a number of
output mechanisms. In some instances, multimodal systems enable a
user to provide multiple types of input to communicate with the
computing system. A communications interface generally enables the
computing device system to communicate with one or more other
computing devices using various communication and network
protocols.
[0117] The preceding disclosure refers to flowcharts and
accompanying descriptions to illustrate the embodiments represented
in the Figures. The disclosed devices, components, and systems
contemplate using or implementing any suitable technique for
performing the steps illustrated. Thus, in the Figures, the
described or similar steps may be performed at any appropriate
time, including concurrently, individually, or in combination. In
addition, many of the steps in the flow charts may take place
simultaneously and/or in different orders than as shown and
described. Moreover, the disclosed systems may use processes and
methods with additional, fewer, and/or different steps.
[0118] Embodiments disclosed herein can be implemented in digital
electronic circuitry, or in computer software, firmware, or
hardware, including the herein disclosed structures and their
equivalents. Some embodiments can be implemented as one or more
computer programs, i.e., one or more modules of computer program
instructions, encoded on computer storage medium for execution by
one or more processors. A computer storage medium can be, or can be
included in, a computer-readable storage device, a
computer-readable storage substrate, or a random or serial access
memory. The computer storage medium can also be, or can be included
in, one or more separate physical components or media such as
multiple CDs, disks, or other storage devices. The computer
readable storage medium does not include a transitory signal.
[0119] The herein disclosed methods can be implemented as
operations performed by a processor on data stored on one or more
computer-readable storage devices or received from other
sources.
[0120] A computer program (also known as a program, module, engine,
software, software application, script, or code) can be written in
any form of programming language, including compiled or interpreted
languages, declarative or procedural languages, and it can be
deployed in any form, including as a stand-alone program or as a
module, component, subroutine, object, or other unit suitable for
use in a computing environment. A computer program may, but need
not, correspond to a file in a file system. A program can be stored
in a portion of a file that holds other programs or data (e.g., one
or more scripts stored in a markup language document), in a single
file dedicated to the program in question, or in multiple
coordinated files (e.g., files that store one or more modules,
sub-programs, or portions of code). A computer program can be
deployed to be executed on one computer or on multiple computers
that are located at one site or distributed across multiple sites
and interconnected by a communication network.
[0121] The terms and descriptions used herein are set forth by way
of illustration only and are not meant as limitations. Those
skilled in the art will recognize that many variations are possible
within the spirit and scope of the invention as defined in the
following claims, and there equivalents, in which all terms are to
be understood in their broadest possible sense unless otherwise
indicated.
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References