U.S. patent application number 15/398789 was filed with the patent office on 2018-07-05 for website domain specific search.
The applicant listed for this patent is INTERNATIONAL BUSINESS MACHINES CORPORATION. Invention is credited to Faheem Altaf, Lisa Seacat DeLuca, Raghuram Srinivas.
Application Number | 20180189403 15/398789 |
Document ID | / |
Family ID | 62712428 |
Filed Date | 2018-07-05 |
United States Patent
Application |
20180189403 |
Kind Code |
A1 |
Altaf; Faheem ; et
al. |
July 5, 2018 |
WEBSITE DOMAIN SPECIFIC SEARCH
Abstract
A method and system for improving a domain specific search is
provided. The method includes executing a user initiated search
query and analyzing associated. In response, a search results data
set is generated and associated hardware sensor devices detect how
a user interacts with specific search facets of the search results
data set. The search results data set is refined and attributes of
the specific search facets are determined. Unstructured data
associated with items described within the search results data set
is updated.
Inventors: |
Altaf; Faheem;
(Pflugerville, TX) ; DeLuca; Lisa Seacat;
(Baltimore, MD) ; Srinivas; Raghuram; (McKinney,
TX) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
INTERNATIONAL BUSINESS MACHINES CORPORATION |
Armonk |
NY |
US |
|
|
Family ID: |
62712428 |
Appl. No.: |
15/398789 |
Filed: |
January 5, 2017 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/9535
20190101 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. A domain specific search improvement method comprising:
executing, by a processor of a hardware device, a user initiated
search query; analyzing, by said processor, results of said
executing; generating, by said processor in response to results of
said executing and said analyzing, a search results data set;
detecting, by said processor enabling hardware sensor devices, how
a user interacts with specific search facets of said search results
data set; refining, by said processor based on results of said
detecting, said search results data set; determining, by said
processor, attributes of said specific search facets of said search
results data set; and updating, by said processor based on results
of said determining, unstructured data associated with items
described within said search results data set.
2. The method of claim 1, further comprising: determining, by said
processor, a value associated with a number of times that said
search facet attributes have been selected in search results data
set executed by additional users.
3. The method of claim 2, further comprising: determining, by said
processor, that said value exceeds a specified threshold; and
combining, by said processor based on results of said determining
that said value exceeds said specified threshold, said attributes
with said first unstructured data.
4. The method of claim 2, further comprising: determining, by said
processor, that said value is less than a specified threshold; and
removing, by said processor based on results of said determining
that said value is less than said specified threshold, said
attributes from said first unstructured data.
5. The method of claim 1, wherein said first unstructured data
comprises natural language pairs and associated attributes.
6. The method of claim 1, wherein said analyzing comprises
executing a keyword extraction process.
7. The method of claim 1, wherein said updating comprises retaining
data of said unstructured data.
8. The method of claim 1, wherein said updating comprises removing
data of said unstructured data.
9. The method of claim 1, further comprising: providing at least
one support service for at least one of creating, integrating,
hosting, maintaining, and deploying computer-readable code in the
hardware device, said code being executed by the computer processor
to implement: said executing, said analyzing, said generating, said
detecting, said refining, said determining, and said updating.
10. A computer program product, comprising a computer readable
hardware storage device storing a computer readable program code,
said computer readable program code comprising an algorithm that
when executed by a processor of a hardware device implements a
domain specific search improvement method, said method comprising:
executing, by said processor, a user initiated search query;
analyzing, by said processor, results of said executing;
generating, by said processor in response to results of said
executing and said analyzing, a search results data set; detecting,
by said processor enabling hardware sensor devices, how a user
interacts with specific search facets of said search results data
set; refining, by said processor based on results of said
detecting, said search results data set; determining, by said
processor, attributes of said specific search facets of said search
results data set; and updating, by said processor based on results
of said determining, unstructured data associated with items
described within said search results data set.
11. The computer program product of claim 10, wherein said method
further comprises: determining, by said processor, a value
associated with a number of times that said search facet attributes
have been selected in search results data set executed by
additional users.
12. The computer program product of claim 11, wherein said method
further comprises: determining, by said processor, that said value
exceeds a specified threshold; and combining, by said processor
based on results of said determining that said value exceeds said
specified threshold, said attributes with said first unstructured
data.
13. The computer program product of claim 11, wherein said method
further comprises: determining, by said processor, that said value
is less than a specified threshold; and removing, by said processor
based on results of said determining that said value is less than
said specified threshold, said attributes from said first
unstructured data.
14. The computer program product of claim 10, wherein said first
unstructured data comprises natural language pairs and associated
attributes.
15. The computer program product of claim 10, wherein said
analyzing comprises executing a keyword extraction process.
16. The computer program product of claim 10, wherein said updating
comprises retaining data of said unstructured data.
17. The computer program product of claim 10, wherein said updating
comprises removing data of said unstructured data.
18. A hardware device comprising a processor coupled to a
computer-readable memory unit, said memory unit comprising
instructions that when executed by the processor executes a domain
specific search improvement method comprising: executing, by said
processor, a user initiated search query; analyzing, by said
processor, results of said executing; generating, by said processor
in response to results of said executing and said analyzing, a
search results data set; detecting, by said processor enabling
hardware sensor devices, how a user interacts with specific search
facets of said search results data set; refining, by said processor
based on results of said detecting, said search results data set;
determining, by said processor, attributes of said specific search
facets of said search results data set; and updating, by said
processor based on results of said determining, unstructured data
associated with items described within said search results data
set.
19. The hardware device of claim 18, wherein said method further
comprises: determining, by said processor, a value associated with
a number of times that said search facet attributes have been
selected in search results data set executed by additional
users.
20. The hardware device of claim 18, wherein said method further
comprises: determining, by said processor, that said value exceeds
a specified threshold; and combining, by said processor based on
results of said determining that said value exceeds said specified
threshold, said attributes with said first unstructured data.
Description
FIELD
[0001] The present invention relates generally to a method for
implementing a domain specific search query and in particular to a
method and associated system for improving search query technology
by determining how a user interacts with specific search facets of
Web based search results and updating unstructured results of the
Web based search results.
BACKGROUND
[0002] Accurately executing a search comprising multiple attributes
typically includes an inaccurate process with little flexibility.
Analyzing multiple attributes with respect to search results may
include a complicated process that may be time consuming and
require a large amount of resources. Accordingly, there exists a
need in the art to overcome at least some of the deficiencies and
limitations described herein above.
SUMMARY
[0003] A first aspect of the invention provides domain specific
search improvement method comprising: executing, by a processor of
a hardware device, a user initiated search query; analyzing, by the
processor, results of the executing; generating, by the processor
in response to results of the executing and the analyzing, a search
results data set; detecting, by the processor enabling hardware
sensor devices, how a user interacts with specific search facets of
the search results data set; refining, by the processor based on
results of the detecting, the search results data set; determining,
by the processor, attributes of the specific search facets of the
search results data set; and updating, by the processor based on
results of the determining, unstructured data associated with items
described within the search results data set.
[0004] A second aspect of the invention provides computer program
product, comprising a computer readable hardware storage device
storing a computer readable program code, the computer readable
program code comprising an algorithm that when executed by a
processor of a hardware device implements a domain specific search
improvement method, the method comprising: executing, by the
processor, a user initiated search query; analyzing, by the
processor, results of the executing; generating, by the processor
in response to results of the executing and the analyzing, a search
results data set; detecting, by the processor enabling hardware
sensor devices, how a user interacts with specific search facets of
the search results data set; refining, by the processor based on
results of the detecting, the search results data set; determining,
by the processor, attributes of the specific search facets of the
search results data set; and updating, by the processor based on
results of the determining, unstructured data associated with items
described within the search results data set.
[0005] A third aspect of the invention provides a hardware device
comprising a processor coupled to a computer-readable memory unit,
the memory unit comprising instructions that when executed by the
processor executes a domain specific search improvement method
comprising: executing, by the processor, a user initiated search
query; analyzing, by the processor, results of the executing;
generating, by the processor in response to results of the
executing and the analyzing, a search results data set; detecting,
by the processor enabling hardware sensor devices, how a user
interacts with specific search facets of the search results data
set; refining, by the processor based on results of the detecting,
the search results data determining, by the processor, attributes
of the specific search facets of the search results data set; and
updating, by the processor based on results of the determining,
unstructured data associated with items described within the search
results data set.
[0006] The present invention advantageously provides a simple
method and associated system capable of accurately executing a
search.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIG. 1 illustrates a system for improving search query
technology by determining how a user interacts with specific search
facets of Web based search results and updating unstructured
results of the Web based search results, in accordance with
embodiments of the present invention.
[0008] FIG. 2 illustrates an algorithm detailing a process flow
enabled by the system of FIG. 1 for improving search query
technology by determining how a user interacts with specific search
facets of Web based search results and updating unstructured
results of the Web based search results, in accordance with
embodiments of the present invention.
[0009] FIG. 3 illustrates an implementation example enabled by the
system of FIG. 1 for improving search query technology by
determining how a user interacts with specific search facets of Web
based search results and updating unstructured results of the Web
based search results, in accordance with embodiments of the present
invention.
[0010] FIG. 4 illustrates a computer system used by the system of
FIG. 1 for enabling a process for improving search query technology
by determining how a user interacts with specific search facets of
Web based search results and updating unstructured results of the
Web based search results, in accordance with embodiments of the
present invention.
[0011] FIG. 5 illustrates a cloud computing environment, in
accordance with embodiments of the present invention.
[0012] FIG. 6 illustrates a set of functional abstraction layers
provided by the cloud computing environment, in accordance with
embodiments of the present invention.
DETAILED DESCRIPTION
[0013] FIG. 1 illustrates a system 100 for improving search query
technology by determining how a user interacts with specific search
facets of Web based search results and updating unstructured
results of the Web based search results, in accordance with
embodiments of the present invention. System 100 enables a process
for determining a candidate set of unstructured Website based
attributes for an item (e.g., a product). Archived user attribute
interactions are analyzed to determine how often the unstructured
Website based attributes have been referenced with respect to
previous natural language searches. Attributes (of the unstructured
Website based attributes) reaching a reference threshold are saved
such that when a subsequent natural language search is executed, a
superior result is achieved as only popular attributes (based on a
popularity of use of the attributes in prior searches) are
considered for the items. Therefore, system 100 executed a process
for analyzing a history of user facet interaction (with items) via
a natural language search to determine the most relevant attributes
for an item. A facet is defined herein as a specific aspect or
feature of an item. System 100 enables a natural language
classifier (NLC) circuit 19 to execute a semantic search associated
with an unstructured data analysis process with respect to search
facet analysis. A semantic search improves a search accuracy by
understanding user interactions in combination with a contextual
meaning of terms as they appear within a searchable dataspace
(e.g., the Internet, a closed system, etc.) to generate more
relevant results.
[0014] System 100 of FIG. 1 includes hardware devices 114a . . .
114n and a user facet interaction data repository 29 in
communication with a hardware apparatus 14 via a network 118.
Hardware devices 114a . . . 114n and hardware apparatus 14 each may
comprise an embedded computer. An embedded computer is defined
herein as a remotely portable dedicated computer comprising a
combination of computer hardware and software (fixed in capability
or programmable) specifically designed for executing a specialized
function. Programmable embedded computers may comprise specialized
programming interfaces. Additionally, hardware devices 114a . . .
114n and hardware apparatus 14 may each comprise a specialized
hardware device comprising specialized (non-generic) hardware and
circuitry (i.e., specialized discrete non-generic analog, digital,
and logic based circuitry) for executing a process described with
respect to FIGS. 1-3. The specialized discrete non-generic analog,
digital, and logic based circuitry may include proprietary
specially designed components (e.g., a specialized integrated
circuit such as a natural language classifier (NLC) circuit 19 and
circuitry and sensors 22 designed for only implementing an
automated process for determining how a user interacts with
specific search facets of Web based search results and updating
unstructured results of the Web based search results. Hardware
apparatus 14 includes a memory system 8, software 17, NLC circuit
19, and circuitry and sensors 22. The memory system 8 (e.g., a
database) and user facet interaction data repository 29 may each
include a single memory system. Alternatively, the memory system 8
and user facet interaction data repository 29 may each include a
plurality of memory systems. Hardware devices 114a . . . 114n may
comprise any type of hardware devices (comprising embedded
circuitry for only performing an automated process for determining
how a user interacts with specific search facets of Web based
search results and updating unstructured results of the Web based
search results including, inter alia, a smart phone, a PDA, a
tablet computer, a laptop computer, etc. Circuitry and sensors 22
may include any type of sensors including, inter alia, GPS sensors,
video recording devices, optical sensors, weight sensors,
temperature sensors, pressure sensors, etc. Additionally, Hardware
devices 114a . . . 114n may comprise any of the aforementioned
sensors for enabling an automated process for determining how a
user interacts with specific search facets of Web based search
results and updating unstructured results of the Web based search
results.
[0015] System 100 of FIG. 1 enables a process for determining item
attribute importance as follows:
[0016] During a process for executing a user initiated search
query, a history associated with user facet interactions is
determined based on previous natural language search queries and a
history of user facet interactions. In response, an attribute for
an item of a specified item category is determined. The attribute
may be comprised by a description of the item and may be identified
as being above a threshold number of instances with respect to
descriptions of products included within the a specified item
category. One or more facets for a category of items may be
determined based the attribute. A set of search results for the
specified item category is presented to a user. The set of search
results for the specified item category is refined based an item
facet selection. The description of the item includes structured
data and one or more unstructured data/value pair attributes may be
generated from the structured data.
[0017] FIG. 2 illustrates an algorithm detailing a process flow
enabled by system 100 of FIG. 1 for improving search query
technology by determining how a user interacts with specific search
facets of Web based search results and updating unstructured
results of the Web based search results, in accordance with
embodiments of the present invention. Each of the steps in the
algorithm of FIG. 2 may be enabled and executed in any order by a
computer processor(s) or any type of specialized hardware executing
specialized computer code. In step 200, a user initiated search
query is executed. In step 202, the results of the user initiated
search query are analyzed (e.g., via execution of a keyword
extraction process). In step 204, a search results data set is
generated based on results of steps 200 and 202. In step 210,
system 100 detects (via sensors) how a user interacts with specific
search facets of the search results data set. In step 212, the
search results data set is refined based on results of step 210. In
step 214, attributes of said specific search facets of the search
results data set are determined. In step 216, unstructured data
associated with items described within the search results data set
are updated based on results of step 214. The update may include,
inter alia, retaining data of the unstructured data, removing data
of the unstructured data, etc. In step 218, a value associated with
a number of times that the search facet attributes have been
selected in search results data set executed by additional users is
determined. Additionally, system 100 determines if the value
exceeds or is less than a specified threshold value. In step 220,
the attributes are: combined with associated unstructured data (if
the specified threshold value exceeds the specified threshold
value) or removed from the associated unstructured data (if the
specified threshold value is less than the specified threshold
value). The associated unstructured data may include natural
language pairs and associated attributes.
[0018] FIG. 3 illustrates an implementation example enabled by
system 100 of FIG. 1 for improving search query technology by
determining how a user interacts with specific search facets of Web
based search results and updating unstructured results of the Web
based search results, in accordance with embodiments of the present
invention. System 100 enables a process for modifying a corpus
(i.e., a large collection of data text such as written or spoken
material upon which a linguistic analysis is based) of data related
to a set of items (e.g., products, services, digital goods or
services, electronic information, etc.) based on user interaction
with associated facets. The example illustrates a product data
catalog 304 (retrieved during a natural language query 310)
comprising a search entry for the term "chainsaw" (i.e., Saw Model
1440). In response, a list of chain saws is returned in combination
with a set of associated facets. A product description for the
chainsaw item comprises structured data. Therefore, the system
(e.g., system 100 of FIG. 1) generates related unstructured
data/value pair attributes 306 from the structured data. For
example: a blade length comprises 14 inches; power is provided by
gasoline; and the color is green. In response, the system maintains
an archive of user attribute interactions with respect to a Website
associated with previous user searches. For example, in multiple
prior natural language searches for chainsaws at the Website, users
associated attributes of "blade length" and "power" very frequently
with chainsaws, but rarely, associated an attribute of "color" with
a chainsaw search. Therefore, attributes of "blade length" and
"power" are flagged as relevant facets for the Web search and
stored in a user attribute interaction archive 308. Likewise, an
attribute of "power" is not determined to be a relevant facet for
the search.
[0019] Additionally, a Webpage illustrating multiple searched
products may present multiple possible facets that may be refined
by, inter alia, a brand, a power source, a chain saw chain length,
a color, etc. In response, users may interact with the facets to
refine the search results. Based on the interactions it is
determined that a majority of users typically refine or interact
with the facets of: power source, brand, and chain saw length and
rarely refine or interact with the facets of color. Therefore, a
resulting corpus is created or modified (i.e., with respect to
facet interaction changes over time) using natural language
attributes. For example, a specific chain saw may comprise a corpus
of: "Brand is Remington. Chain length is 20 inches. Power source is
gasoline. Price is $25. Color is green. Weight is 6.2 lbs. Warranty
is 5 years". System 100 monitors user interactions and determines
that the top facets are: Brand, Chain length, and Price.
Additionally, system 100 determines the facets of: Color and Weight
do not typically comprise facets associated with user interactions.
Therefore, overtime as the aforementioned facet interactions
change, a natural language corpus entry may additionally change
based on a computer hardware/software based self-learning process
and in response, the entries of: "color is green" "weight is 6.2
lbs." are removed from search results thereby improving a search
time and accuracy resulting in an improved (i.e., faster) search
process based on the refined (i.e., smaller and more specific)
corpus content. The improved corpus content prevents hardware
apparatus 14 (of FIG. 1) from evaluating a large amount of
irrelevant information. Therefore, based on tailoring process with
respect to the facets, superior search results may be presented to
the user. For example, a speed at which system 100 (hardware
apparatus 14) is able to locate information is significantly faster
when only relevant information is available within the corpus.
Likewise, system 100 is enabled (via a training or iterative
learning process) such that hardware and software of the system is
improved over time via a process to determine information relevant
to different types of products/items/searches such that a hardware
and software functionality is improved thereby improving an
operation of hardware apparatus 14 of FIG. 1.
[0020] FIG. 4 illustrates a computer system 90 (e.g., hardware
devices 114a . . . 114n and hardware apparatus 14) used by or
comprised by the system of FIG. 1 for improving search query
technology by determining how a user interacts with specific search
facets of Web based search results and updating unstructured
results of the Web based search results, in accordance with
embodiments of the present invention.
[0021] Aspects of the present invention may take the form of an
entirely hardware embodiment, an entirely software embodiment
(including firmware, resident software, micro-code, etc.) or an
embodiment combining software and hardware aspects that may all
generally be referred to herein as a "circuit," "module," or
"system."
[0022] The present invention may be a system, a method, and/or a
computer program product. The computer program product may include
a computer readable storage medium (or media) having computer
readable program instructions thereon for causing a processor to
carry out aspects of the present invention.
[0023] The computer readable storage medium can be a tangible
device that can retain and store instructions for use by an
instruction execution device. The computer readable storage medium
may be, for example, but is not limited to, an electronic storage
device, a magnetic storage device, an optical storage device, an
electromagnetic storage device, a semiconductor storage device, or
any suitable combination of the foregoing. A non-exhaustive list of
more specific examples of the computer readable storage medium
includes the following: a portable computer diskette, a hard disk,
a random access memory (RAM), a read-only memory (ROM), an erasable
programmable read-only memory (EPROM or Flash memory), a static
random access memory (SRAM), a portable compact disc read-only
memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a
floppy disk, a mechanically encoded device such as punch-cards or
raised structures in a groove having instructions recorded thereon,
and any suitable combination of the foregoing. A computer readable
storage medium, as used herein, is not to be construed as being
transitory signals per se, such as radio waves or other freely
propagating electromagnetic waves, electromagnetic waves
propagating through a waveguide or other transmission media (e.g.,
light pulses passing through a fiber-optic cable), or electrical
signals transmitted through a wire.
[0024] Computer readable program instructions described herein can
be downloaded to respective computing/processing devices from a
computer readable storage medium or to an external computer or
external storage device via a network, for example, the Internet, a
local area network, a wide area network and/or a wireless network.
The network may comprise copper transmission cables, optical
transmission fibers, wireless transmission, routers, firewalls,
switches, gateway computers and/or edge servers. A network adapter
card or network interface in each computing/processing apparatus
receives computer readable program instructions from the network
and forwards the computer readable program instructions for storage
in a computer readable storage medium within the respective
computing/processing device.
[0025] Computer readable program instructions for carrying out
operations of the present invention may be assembler instructions,
instruction-set-architecture (ISA) instructions, machine
instructions, machine dependent instructions, microcode, firmware
instructions, state-setting data, or either source code or object
code written in any combination of one or more programming
languages, including an object oriented programming language such
as Smalltalk, C++ or the like, and conventional procedural
programming languages, such as the "C" programming language or
similar programming languages. The computer readable program
instructions may execute entirely on the user's computer, partly on
the user's computer, as a stand-alone software package, partly on
the user's computer and partly on a remote computer or entirely on
the remote computer or server. In the latter scenario, the remote
computer may be connected to the user's computer through any type
of network, including a local area network (LAN) or a wide area
network (WAN), or the connection may be made to an external
computer (for example, through the Internet using an Internet
Service Provider). In some embodiments, electronic circuitry
including, for example, programmable logic circuitry,
field-programmable gate arrays (FPGA), or programmable logic arrays
(PLA) may execute the computer readable program instructions by
utilizing state information of the computer readable program
instructions to personalize the electronic circuitry, in order to
perform aspects of the present invention.
[0026] Aspects of the present invention are described herein with
reference to flowchart illustrations and/or block diagrams of
methods, device (systems), and computer program products according
to embodiments of the invention. It will be understood that each
block of the flowchart illustrations and/or block diagrams, and
combinations of blocks in the flowchart illustrations and/or block
diagrams, can be implemented by computer readable program
instructions.
[0027] These computer readable program instructions may be provided
to a processor of a general purpose computer, special purpose
computer, or other programmable data processing device to produce a
machine, such that the instructions, which execute via the
processor of the computer or other programmable data processing
device, create means for implementing the functions/acts specified
in the flowchart and/or block diagram block or blocks. These
computer readable program instructions may also be stored in a
computer readable storage medium that can direct a computer, a
programmable data processing device, and/or other devices to
function in a particular manner, such that the computer readable
storage medium having instructions stored therein comprises an
article of manufacture including instructions which implement
aspects of the function/act specified in the flowchart and/or block
diagram block or blocks.
[0028] The computer readable program instructions may also be
loaded onto a computer, other programmable data processing device,
or other device to cause a series of operational steps to be
performed on the computer, other programmable device or other
device to produce a computer implemented process, such that the
instructions which execute on the computer, other programmable
device, or other device implement the functions/acts specified in
the flowchart and/or block diagram block or blocks.
[0029] The flowchart and block diagrams in the Figures illustrate
the architecture, functionality, and operation of possible
implementations of systems, methods, and computer program products
according to various embodiments of the present invention. In this
regard, each block in the flowchart or block diagrams may represent
a module, segment, or portion of instructions, which comprises one
or more executable instructions for implementing the specified
logical function(s). In some alternative implementations, the
functions noted in the block may occur out of the order noted in
the figures. For example, two blocks shown in succession may, in
fact, be executed substantially concurrently, or the blocks may
sometimes be executed in the reverse order, depending upon the
functionality involved. It will also be noted that each block of
the block diagrams and/or flowchart illustration, and combinations
of blocks in the block diagrams and/or flowchart illustration, can
be implemented by special purpose hardware-based systems that
perform the specified functions or acts or carry out combinations
of special purpose hardware and computer instructions.
[0030] The computer system 90 illustrated in FIG. 4 includes a
processor 91, an input device 92 coupled to the processor 91, an
output device 93 coupled to the processor 91, and memory devices 94
and 95 each coupled to the processor 91. The input device 92 may
be, inter alia, a keyboard, a mouse, a camera, a touchscreen, etc.
The output device 93 may be, inter alia, a printer, a plotter, a
computer screen, a magnetic tape, a removable hard disk, a floppy
disk, etc. The memory devices 94 and 95 may be, inter alia, a hard
disk, a floppy disk, a magnetic tape, an optical storage such as a
compact disc (CD) or a digital video disc (DVD), a dynamic random
access memory (DRAM), a read-only memory (ROM), etc. The memory
device 95 includes a computer code 97. The computer code 97
includes algorithms (e.g., the algorithm of FIG. 2) for enabling a
process for improving search query technology by determining how a
user interacts with specific search facets of Web based search
results and updating unstructured results of the Web based search
results. The processor 91 executes the computer code 97. The memory
device 94 includes input data 96. The input data 96 includes input
required by the computer code 97. The output device 93 displays
output from the computer code 97. Either or both memory devices 94
and 95 (or one or more additional memory devices such as read only
memory device 96) may include algorithms (e.g., the algorithm of
FIG. 2) and may be used as a computer usable medium (or a computer
readable medium or a program storage device) having a computer
readable program code embodied therein and/or having other data
stored therein, wherein the computer readable program code includes
the computer code 97. Generally, a computer program product (or,
alternatively, an article of manufacture) of the computer system 90
may include the computer usable medium (or the program storage
device).
[0031] In some embodiments, rather than being stored and accessed
from a hard drive, optical disc or other writeable, rewriteable, or
removable hardware memory device 95, stored computer program code
84 (e.g., including the algorithm of FIG. 2) may be stored on a
static, nonremovable, read-only storage medium such as a Read-Only
Memory (ROM) device 85, or may be accessed by processor 91 directly
from such a static, nonremovable, read-only medium 85. Similarly,
in some embodiments, stored computer program code 97 may be stored
as computer-readable firmware 85, or may be accessed by processor
91 directly from such firmware 85, rather than from a more dynamic
or removable hardware data-storage device 95, such as a hard drive
or optical disc.
[0032] Still yet, any of the components of the present invention
could be created, integrated, hosted, maintained, deployed,
managed, serviced, etc. by a service supplier who offers to enable
a process for improving search query technology by determining how
a user interacts with specific search facets of Web based search
results and updating unstructured results of the Web based search
results. Thus, the present invention discloses a process for
deploying, creating, integrating, hosting, maintaining, and/or
integrating computing infrastructure, including integrating
computer-readable code into the computer system 90, wherein the
code in combination with the computer system 90 is capable of
performing a method for enabling a process for improving search
query technology by determining how a user interacts with specific
search facets of Web based search results and updating unstructured
results of the Web based search results. In another embodiment, the
invention provides a business method that performs the process
steps of the invention on a subscription, advertising, and/or fee
basis. That is, a service supplier, such as a Solution Integrator,
could offer to enable a process for improving search query
technology by determining how a user interacts with specific search
facets of Web based search results and updating unstructured
results of the Web based search results. In this case, the service
supplier can create, maintain, support, etc. a computer
infrastructure that performs the process steps of the invention for
one or more customers. In return, the service supplier can receive
payment from the customer(s) under a subscription and/or fee
agreement and/or the service supplier can receive payment from the
sale of advertising content to one or more third parties.
[0033] While FIG. 4 shows the computer system 90 as a particular
configuration of hardware and software, any configuration of
hardware and software, as would be known to a person of ordinary
skill in the art, may be utilized for the purposes stated supra in
conjunction with the particular computer system 90 of FIG. 4. For
example, the memory devices 94 and 95 may be portions of a single
memory device rather than separate memory devices.
Cloud Computing Environment
[0034] It is to be understood that although this disclosure
includes a detailed description on cloud computing, implementation
of the teachings recited herein are not limited to a cloud
computing environment. Rather, embodiments of the present invention
are capable of being implemented in conjunction with any other type
of computing environment now known or later developed.
[0035] Cloud computing is a model of service delivery for enabling
convenient, on-demand network access to a shared pool of
configurable computing resources (e.g., networks, network
bandwidth, servers, processing, memory, storage, applications,
virtual machines, and services) that can be rapidly provisioned and
released with minimal management effort or interaction with a
provider of the service. This cloud model may include at least five
characteristics, at least three service models, and at least four
deployment models.
[0036] Characteristics are as follows:
[0037] On-demand self-service: a cloud consumer can unilaterally
provision computing capabilities, such as server time and network
storage, as needed automatically without requiring human
interaction with the service's provider.
[0038] Broad network access: capabilities are available over a
network and accessed through standard mechanisms that promote use
by heterogeneous thin or thick client platforms (e.g., mobile
phones, laptops, and PDAs).
[0039] Resource pooling: the provider's computing resources are
pooled to serve multiple consumers using a multi-tenant model, with
different physical and virtual resources dynamically assigned and
reassigned according to demand. There is a sense of location
independence in that the consumer generally has no control or
knowledge over the exact location of the provided resources but may
be able to specify location at a higher level of abstraction (e.g.,
country, state, or datacenter).
[0040] Rapid elasticity: capabilities can be rapidly and
elastically provisioned, in some cases automatically, to quickly
scale out and rapidly released to quickly scale in. To the
consumer, the capabilities available for provisioning often appear
to be unlimited and can be purchased in any quantity at any
time.
[0041] Measured service: cloud systems automatically control and
optimize resource use by leveraging a metering capability at some
level of abstraction appropriate to the type of service (e.g.,
storage, processing, bandwidth, and active user accounts). Resource
usage can be monitored, controlled, and reported, providing
transparency for both the provider and consumer of the utilized
service.
[0042] Service Models are as follows:
[0043] Software as a Service (SaaS): the capability provided to the
consumer is to use the provider's applications running on a cloud
infrastructure. The applications are accessible from various client
devices through a thin client interface such as a web browser
(e.g., web-based e-mail). The consumer does not manage or control
the underlying cloud infrastructure including network, servers,
operating systems, storage, or even individual application
capabilities, with the possible exception of limited user-specific
application configuration settings.
[0044] Platform as a Service (PaaS): the capability provided to the
consumer is to deploy onto the cloud infrastructure
consumer-created or acquired applications created using programming
languages and tools supported by the provider. The consumer does
not manage or control the underlying cloud infrastructure including
networks, servers, operating systems, or storage, but has control
over the deployed applications and possibly application hosting
environment configurations.
[0045] Infrastructure as a Service (IaaS): the capability provided
to the consumer is to provision processing, storage, networks, and
other fundamental computing resources where the consumer is able to
deploy and run arbitrary software, which can include operating
systems and applications. The consumer does not manage or control
the underlying cloud infrastructure but has control over operating
systems, storage, deployed applications, and possibly limited
control of select networking components (e.g., host firewalls).
[0046] Deployment Models are as follows:
[0047] Private cloud: the cloud infrastructure is operated solely
for an organization. It may be managed by the organization or a
third party and may exist on-premises or off-premises.
[0048] Community cloud: the cloud infrastructure is shared by
several organizations and supports a specific community that has
shared concerns (e.g., mission, security requirements, policy, and
compliance considerations). It may be managed by the organizations
or a third party and may exist on-premises or off-premises.
[0049] Public cloud: the cloud infrastructure is made available to
the general public or a large industry group and is owned by an
organization selling cloud services.
[0050] Hybrid cloud: the cloud infrastructure is a composition of
two or more clouds (private, community, or public) that remain
unique entities but are bound together by standardized or
proprietary technology that enables data and application
portability (e.g., cloud bursting for load-balancing between
clouds).
[0051] A cloud computing environment is service oriented with a
focus on statelessness, low coupling, modularity, and semantic
interoperability. At the heart of cloud computing is an
infrastructure that includes a network of interconnected nodes.
[0052] Referring now to FIG. 5, illustrative cloud computing
environment 50 is depicted. As shown, cloud computing environment
50 includes one or more cloud computing nodes 10 with which local
computing devices used by cloud consumers, such as, for example,
personal digital assistant (PDA) or cellular telephone 54A, desktop
computer 54B, laptop computer 54C, and/or automobile computer
system 54N may communicate. Nodes 10 may communicate with one
another. They may be grouped (not shown) physically or virtually,
in one or more networks, such as Private, Community, Public, or
Hybrid clouds as described hereinabove, or a combination thereof.
This allows cloud computing environment 50 to offer infrastructure,
platforms and/or software as services for which a cloud consumer
does not need to maintain resources on a local computing device. It
is understood that the types of computing devices 54A, 54B, 54C and
54N shown in FIG. 8 are intended to be illustrative only and that
computing nodes 10 and cloud computing environment 50 can
communicate with any type of computerized device over any type of
network and/or network addressable connection (e.g., using a web
browser).
[0053] Referring now to FIG. 6, a set of functional abstraction
layers provided by cloud computing environment 50 (see FIG. 5) is
shown. It should be understood in advance that the components,
layers, and functions shown in FIG. 6 are intended to be
illustrative only and embodiments of the invention are not limited
thereto. As depicted, the following layers and corresponding
functions are provided:
[0054] Hardware and software layer 60 includes hardware and
software components. Examples of hardware components include:
mainframes 61; RISC (Reduced Instruction Set Computer) architecture
based servers 62; servers 63; blade servers 64; storage devices 65;
and networks and networking components 66. In some embodiments,
software components include network application server software 67
and database software 68.
[0055] Virtualization layer 70 provides an abstraction layer from
which the following examples of virtual entities may be provided:
virtual servers 71; virtual storage 72; virtual networks 73,
including virtual private networks; virtual applications and
operating systems 74; and virtual clients 75.
[0056] In one example, management layer 80 may provide the
functions described below. Resource provisioning 81 provides
dynamic procurement of computing resources and other resources that
are utilized to perform tasks within the cloud computing
environment. Metering and Pricing 82 provide cost tracking as
resources are utilized within the cloud computing environment, and
billing or invoicing for consumption of these resources. In one
example, these resources may include application software licenses.
Security provides identity verification for cloud consumers and
tasks, as well as protection for data and other resources. User
portal 83 provides access to the cloud computing environment for
consumers and system administrators. Service level management 84
provides cloud computing resource allocation and management such
that required service levels are met. Service Level Agreement (SLA)
planning and fulfillment 85 provide pre-arrangement for, and
procurement of, cloud computing resources for which a future
requirement is anticipated in accordance with an SLA.
[0057] Workloads layer 89 provides examples of functionality for
which the cloud computing environment may be utilized. Examples of
workloads and functions which may be provided from this layer
include: mapping and navigation 91; software development and
lifecycle management 92; virtual classroom education delivery 93;
data analytics processing 94; transaction processing 95; and for
improving search query technology by determining how a user
interacts with specific search facets of Web based search results
and updating unstructured results of the Web based search
results.
[0058] While embodiments of the present invention have been
described herein for purposes of illustration, many modifications
and changes will become apparent to those skilled in the art.
Accordingly, the appended claims are intended to encompass all such
modifications and changes as fall within the true spirit and scope
of this invention.
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