U.S. patent application number 11/268868 was filed with the patent office on 2006-03-09 for hierarchical data-driven navigation system and method for information retrieval.
This patent application is currently assigned to Endeca Technologies, Inc.. Invention is credited to Adam J. Ferrari, David Gourley, Keith Johnson, Frederick C. Knabe, Daniel Tunkelang, John S. Walter.
Application Number | 20060053104 11/268868 |
Document ID | / |
Family ID | 24291434 |
Filed Date | 2006-03-09 |
United States Patent
Application |
20060053104 |
Kind Code |
A1 |
Ferrari; Adam J. ; et
al. |
March 9, 2006 |
Hierarchical data-driven navigation system and method for
information retrieval
Abstract
A data-driven, hierarchical information navigation system and
method enable search of sets of documents or other materials by
certain common attributes that characterize the materials. The
invention includes several aspects of a data-driven, hierarchical
navigation system that employs this navigation mode. The navigation
system of the present invention includes features of an interface,
a knowledge base and a taxonomy definition process and a
classification process for generating the knowledge base, a
graph-based navigable data structure and method for generating the
data structure, World Wide Web-based applications of the system,
and methods of implementing the system. Users are able to search or
browse a particular collection of documents by selecting desired
values for the attributes. A data-driven, hierarchical information
navigation system and method enable this navigation mode by
associating terms with the materials, defining a set of
hierarchical relationships among the terms, and providing a guided
search mechanism based on the relationship between the terms.
Inventors: |
Ferrari; Adam J.;
(Cambridge, MA) ; Gourley; David; (Cambridge,
MA) ; Johnson; Keith; (Newton, MA) ; Knabe;
Frederick C.; (Boston, MA) ; Tunkelang; Daniel;
(Cambridge, MA) ; Walter; John S.; (Boston,
MA) |
Correspondence
Address: |
WILMER CUTLER PICKERING HALE AND DORR LLP
60 STATE STREET
BOSTON
MA
02109
US
|
Assignee: |
Endeca Technologies, Inc.
Cambridge
MA
02142
|
Family ID: |
24291434 |
Appl. No.: |
11/268868 |
Filed: |
November 8, 2005 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
09573305 |
May 18, 2000 |
|
|
|
11268868 |
Nov 8, 2005 |
|
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|
Current U.S.
Class: |
1/1 ;
707/999.003; 707/E17.111 |
Current CPC
Class: |
G06F 3/0482 20130101;
Y10S 707/99943 20130101; G06F 16/00 20190101; G06F 16/2428
20190101; Y10S 707/962 20130101; Y10S 707/99933 20130101; G06F
16/3323 20190101; Y10S 707/99935 20130101; G06F 16/954 20190101;
Y10S 707/99932 20130101 |
Class at
Publication: |
707/003 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. A computer-implemented method for enabling a user to browse
information, the method comprising: storing a plurality of
attribute-value pairs associated with a collection of materials,
wherein each of a plurality of values has an association with at
least one of a plurality of attributes characterizing the
materials; displaying a free-text search box; accepting a search
term entered in the free-text search box; determining the
attribute-value pairs that match the search term; displaying a
representation of the matching attribute-value pairs for the search
term; accepting a selection of an initial set of one or more of the
matching attribute-value pairs; entering a first navigation state
corresponding to a first set of attribute-value pairs including at
least the initial set of matching attribute-value pairs and to a
first particular subset of the materials, the first particular
subset of the materials consisting of those materials in the
collection of materials that are each described by every
attribute-value pair in the first set of attribute-value pairs; and
entering a second navigation state in response to a user action,
the second navigation state corresponding to a second set of
attribute-value pairs and to a second particular subset of the
materials, the second set including at least two mutually
incomparable attribute-value pairs, the second particular subset of
the materials consisting of those materials in the collection of
materials that are each described by every attribute-value pair in
the second set of attribute-value pairs.
2. The method of claim 1, wherein the second set of attribute-value
pairs includes an attribute-value pair that represents a refinement
of the value of an attribute-value pair within the first set of
attribute-value pairs.
3. The method of claim 1, wherein the second set of attribute-value
pairs includes an attribute-value pair that represents a
generalization of the value of an attribute-value pair within the
first set of attribute-value pairs.
4. The method of claim 1, further comprising deselecting an
attribute-value pair from the first set of attribute-value pairs to
obtain the second set of attribute-value pairs.
5. The method of claim 1, wherein the first particular subset of
the materials includes an integrally navigable subset of the
collection of materials.
6. The method of claim 5, wherein within the integrally navigable
subset of the collection of materials at least one of the materials
also belongs to a second integrally navigable subset of the
collection of materials.
7. The method of claim 1, further comprising presenting navigation
options for selection from the first navigation state, the
navigation options including refinements of the first set of
attribute-value pairs.
8. The method of claim 1, further comprising presenting navigation
options for selection from the first navigation state, the
navigation options including lists of attribute-value pairs, each
list corresponding to one of the plurality of attributes.
9. A computer-implemented method for enabling a user to browse
information, the method comprising: storing a plurality of
attribute-value pairs associated with a collection of materials,
wherein each of a plurality of values has an association with at
least one of a plurality of attributes characterizing the
materials; displaying a free-text search box; accepting a search
term entered in the free-text search box; determining the
attribute-value pairs that match the search term; displaying a
representation of the matching attribute-value pairs for the search
term; accepting a selection of a selected set of one or more of the
matching attribute-value pairs; and entering a first navigation
state corresponding to a first set of attribute-value pairs
including at least the selected set of matching attribute-value
pairs and to a first particular subset of the materials, the first
set of attribute-value pairs including at least two mutually
incomparable attribute-value pairs, the first particular subset of
the materials consisting of those materials in the collection of
materials that are each described by every attribute-value pair in
the first set of attribute-value pairs.
10. A computer program product, residing on a computer-readable
medium, for use in browsing information associated with a
collection of materials, the computer program product comprising
instructions for causing a computer to: access a data structure
containing a plurality of attribute-value pairs associated with the
materials, wherein each of a plurality of values has an association
with at least one of a plurality of attributes characterizing the
materials; display a free-text search box; accept a search term
entered in the free-text search box; determine the attribute-value
pairs that match the search term; display a representation of the
matching attribute-value pairs for the search term; accept a
selection of a selected set of one or more of the matching
attribute-value pairs; enter a first navigation state corresponding
to a first set of attribute-value pairs including at least the
selected set of one or more matching attribute-value pairs and to a
particular subset of the materials, the particular subset of the
materials consisting of those materials in the collection of
materials that are each described by every attribute-value pair in
the first set of attribute-value pairs; and enter a second
navigation state in response to a user action, the second
navigation state corresponding to a second set of attribute-value
pairs and to a second particular subset of the materials, the
second set including at least two mutually incomparable
attribute-value pairs, the second particular subset of the
materials consisting of those materials in the collection of
materials that are each described by every attribute-value pair in
the second set of attribute-value pairs.
11. The computer program product of claim 10, wherein some of the
attribute-value pairs in the data structure refine other of the
attribute-value pairs.
12. The computer program product of claim 11, wherein the second
set of attribute-value pairs includes an attribute-value pair that
represents a refinement of the value of an attribute-value pair
within the first set of attribute-value pairs.
Description
1. CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a division of co-pending U.S. patent
application Ser. No. 09/573,305 filed May 18, 2000, and entitled
Hierarchical Data-Driven Navigation System And Method For
Information Retrieval.
2. FIELD OF THE INVENTION
[0002] The present invention generally relates to information
navigation systems and search engines.
3. BACKGROUND OF THE INVENTION
[0003] Information retrieval from a database of information is an
increasingly challenging problem, particularly on the World Wide
Web (WWW), as increased computing power and networking
infrastructure allow the aggregation of large amounts of
information and widespread access to that information. A goal of
the information retrieval process is to allow the identification of
materials of interest to users.
[0004] As the number of materials that users may search increases,
identifying materials relevant to the search becomes increasingly
important, but also increasingly difficult. Challenges posed by the
information retrieval process include providing an intuitive,
flexible user interface and completely and accurately identifying
materials relevant to the user's needs within a reasonable amount
of time. The information retrieval process comprehends two
interrelated technical aspects, namely, information organization
and access.
[0005] Current information navigation systems usually follow one of
three paradigms. One type of information navigation system employs
a database query system. In a typical database query system, a user
formulates a structured query by specifying values for fixed data
fields, and the system enumerates the documents whose data fields
contain those values. PriceSCAN.com uses such an interface, for
example. Generally, a database query system presents users with a
form-based interface, converts the form input into a query in a
formal database language, such as SQL, and then executes the query
on a relational database management system. Disadvantages of
typical query-based systems include that they allow users to make
queries that return no documents and that they offer query
modification options that lead only to further restriction of the
result set (the documents that correspond to the user's search
specifications), rather than to expansion or extension of the
result set.
[0006] A second type of information navigation system is a
free-text search engine. In a typical free-text search engine, the
user enters an arbitrary text string, often in the form of a
Boolean expression, and the system responds by enumerating the
documents that contain matching text. Google.com, for example,
includes a free-text search engine. Generally a free-text search
engine presents users with a search form, often a single line, and
processes queries using a precomputed index. Generally this index
associates each document with a large portion of the words
contained in that document, without substantive consideration of
the document's content. Accordingly, the result set is often a
voluminous, disorganized list that mixes relevant and irrelevant
documents. Although variations have been developed that attempt to
determine the objective of the user's query and to provide
relevance rankings to the result set or to otherwise narrow or
organize the result set, these systems are limited and unreliable
in achieving these objectives.
[0007] A third type of information navigation system is a
tree-based directory. In a tree-based directory, the user generally
starts at the root node of the tree and specifies a query by
successively selecting refining branches that lead to other nodes
in the tree. Shopping.yahoo.com uses a tree-based directory, for
example. In a typical implementation, the hard-coded tree is stored
in a data structure, and the same or another data structure maps
documents to the node or nodes of the tree where they are located.
A particular document is typically accessible from only one or, at
most, a few, paths through the tree. The collection of navigation
states is relatively static--while documents are commonly added to
nodes in the directory, the structure of the directory typically
remains the same. In a pure tree-based directory, the directory
nodes are arranged such that there is a single root node from which
all users start, and every other directory node can only be reached
via a unique sequence of branches that the user selects from the
root node. Such a directory imposes the limitation that the
branches of the tree must be navigationally disjoint--even though
the way that documents are assigned to the disjoint branches may
not be intuitive to users. It is possible to address this rigidity
by adding additional links to convert the tree to a directed
acyclic graph. Updating the directory structure remains a difficult
task, and leaf nodes are especially prone to end up with large
numbers of corresponding documents.
[0008] In all of these types of navigation systems, it may be
difficult for a user to revise a query effectively after viewing
its result set. In a database query system, users can add or remove
terms from the query, but it is generally difficult for users to
avoid underspecified queries (i.e. too many results) or
overspecified queries (i.e. no results). The same problem arises in
free-text search engines. In tree-based directories, the only means
for users to revise a query is either to narrow it by selecting a
branch or to generalize it by backing up to a previous branch.
[0009] Various other systems for information retrieval are also
available. For example. U.S. Pat. Nos. 5,715,444 and 5,983,219 to
Danish et al., both entitled "Method and System for Executing a
Guided Parametric Search," disclose an interface for identifying a
single item from a family of items. The interface provides users
with a set of lists of features present in the family of items and
identifies items that satisfy selected features.
4. SUMMARY OF THE INVENTION
[0010] The present invention, a hierarchical, data-driven
information navigation system and method, enables the navigation of
a collection of documents or other materials using certain common
attributes associated with those materials. The navigation system
interface allows the user to select values for the attributes
associated with the materials in the current navigation state and
returns the materials that correspond to the user's selections. The
present invention enables this navigation mode by associating terms
(attribute-value pairs) with the documents, defining a set of
hierarchical refinement relationships (i.e., a partial order) among
the terms, and providing a guided navigation mechanism based on the
association of terms with documents and the relationships among the
terms.
[0011] The present invention includes several components and
features relating to a hierarchical data-driven navigation system.
Among these are a user interface, a knowledge base, a process for
generating and maintaining the knowledge base, a navigable data
structure and method for generating the data structure, WWW-based
applications of the system, and methods of implementing the system.
Although the invention is described herein primarily with reference
to a WWW-based system for navigating a product database, it should
be understood that a similar navigation system could be employed in
any database context where materials may be associated with terms
and users can identify materials of interest by way of those
terms.
[0012] The present invention uses a knowledge base of information
regarding the collection of materials to formulate and to adapt the
interface to guide the user through the collection of navigation
states by providing relevant navigation options. The knowledge base
includes an enumeration of attributes relevant to the materials, a
range of values for each attribute, and a representation of the
partial order that relates terms (the attribute-value pairs).
Attribute-value pairs for materials relating to entertainment, for
example, may be Products: Movies and Director: Spike Lee.
(Attribute-value pairs are represented throughout this
specification in this Attribute: Value format; navigation states
are represented as bracketed sets of attribute-value pairs.) The
knowledge base also includes a classification mapping that
associates each item in the collection of materials with a set of
terms that characterize that item.
[0013] The knowledge base is typically organized by domains, which
are sets of materials that conform to natural groupings.
Preferably, a domain is chosen such that a manageable number of
attributes suffice to effectively distinguish and to navigate among
the materials in that domain. The knowledge base preferably
includes a characterization of each domain, which might include
rules or default expectations concerning the classification of
documents in that domain. A particular item may be in more than one
domain.
[0014] The present invention includes a user interface for
navigation. The user interface preferably presents the user's
navigation state as a set of terms organized by attribute. For a
given set of terms, the user interface presents materials that are
associated with those terms and presents relevant navigation
options for narrowing or for generalizing the navigation state. In
one aspect of the present invention, users navigate through the
collection of materials by selecting and deselecting terms.
[0015] In one aspect of the present invention, the user interface
responds immediately to the selection or the deselection of terms,
rather than waiting for the user to construct and to submit a
comprehensive query composed of multiple terms. Once a query has
been executed, the user may narrow the navigation state by
selecting additional terms, or by refining existing terms.
Alternatively, the user may broaden the navigation state by
deselecting terms that have already been selected or by
generalizing the terms. In preferred embodiments, the user may
broaden the navigation state by deselecting terms in an order
different from that in which they were selected. For example, a
user could start at {Products: Movies}, narrow by selecting an
additional term to {Products: Movies; Genre: Drama}, narrow again
to {Products: Movies; Genre: Drama; Director: Spike Lee}, and then
broaden by deselecting a term to {Products: Movies; Director: Spike
Lee}.
[0016] In another aspect of the present invention, the user
interface allows users to use free-text search to find terms of
interest. In another aspect of the present invention, the user
interface also allows users to use free-text search on descriptive
information associated with the materials.
[0017] In another aspect of the present invention, the user
interface presents users with context-dependent navigation options
for narrowing the navigation state. The user interface does not
present the user with terms whose selection would correspond to no
documents in the resulting navigation state. The user interface
presents the user only with terms that are associated with at least
one item in the present navigation state. Also, the user interface
presents new navigation options as they become relevant. The
knowledge base may contain rules that determine when particular
attributes or terms are made available to users for navigation.
[0018] In another aspect of the invention--for example, when the
materials correspond to products available for purchase from
various sources--the knowledge base includes a catalog of canonical
representations that have been aggregated from the materials.
[0019] In another aspect of the invention, the knowledge base may
include definitions of stores, sets of materials that are grouped
to be searchable at one time. A store may include documents from
one or more domains. An item may be assigned to more than one
store. The knowledge base may also include rules to customize
navigation for particular stores.
[0020] In another aspect of the invention, the knowledge base is
developed through a multi-stage, iterative process. Workflow
management allocates resources to maximize the efficiency of
generating and of maintaining the knowledge base.
[0021] The knowledge base is used to generate data structures that
support navigation through a collection of materials. In one aspect
of the invention, the navigation system consists of a hierarchy
(i.e., a partial order) of navigation states that map sets of terms
to the sets of materials with which those terms are associated. In
another aspect of the invention, the navigation states are related
by transitions corresponding to terms used to narrow from one
navigation state to another. The navigation states may be fully or
partially precomputed, or may be entirely computed at run-time.
5. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The invention, including these and other features thereof,
may be more fully understood from the following description and
accompanying drawings, in which:
[0023] FIG. 1 is a view of a user interface to a navigation system
in accordance with an embodiment of the present invention.
[0024] FIG. 2 is a view of the user interface of FIG. 1, showing a
drop-down pick list of navigable terms.
[0025] FIG. 3 is a view of the user interface of FIG. 1, showing a
navigation state.
[0026] FIG. 4 is a view of the user interface of FIG. 1, showing a
navigation state.
[0027] FIG. 5 is a view of the user interface of FIG. 1, showing a
navigation state.
[0028] FIG. 6 is a view of the user interface of FIG. 1, showing a
navigation state.
[0029] FIG. 7 is a view of the user interface of FIG. 1, showing a
navigation state.
[0030] FIG. 8 is a view of the user interface of FIG. 1, showing a
navigation state.
[0031] FIG. 9 is a view of the user interface of FIG. 1, showing
the result of a free-text search for terms.
[0032] FIG. 10 is a view of the user interface of FIG. 1, showing
information about a particular document.
[0033] FIGS. 11A-C are representative examples of how the range of
values for an attribute could be partially ordered in accordance
with an embodiment of the present invention.
[0034] FIG. 12 is a block diagram of a process for collecting and
classifying documents in accordance with an embodiment of the
present invention.
[0035] FIG. 13 is a table illustrating how a set of documents may
be classified in accordance with an embodiment of the present
invention.
[0036] FIG. 14 is a representative partial order of navigation
states in accordance with an embodiment of the present
invention.
[0037] FIG. 15 is a block diagram of a process for precomputing a
navigation state in accordance with an embodiment of the present
invention.
6. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0038] User Interface
[0039] In accordance with one embodiment of the present invention,
FIG. 1 shows a user interface 10 to a hierarchical, data-driven
navigation system. The navigation system operates on a collection
of documents defined in a knowledge base. As is shown, the user is
preferably presented with at least two alternative methods of using
the navigation system: (1) by selecting terms to navigate through
the collection of documents, or (2) by entering a desired keyword
in a search box.
[0040] The navigation system preferably organizes documents by
domain. In accordance with one embodiment of the present invention,
the user interface 10 shown in FIGS. 1-10 is operating on a set of
documents that are part of a wine domain. Preferably, a domain
defines a portion of the collection of documents that reflects a
natural grouping. Generally, the set of attributes used to classify
documents in a domain will be a manageable subset of the attributes
used to classify the entire collection of documents. A domain
definition may be a type of product, e.g., wines or consumer
electronics. A domain may be divided into subdomains to further
organize the collection of documents. For example, there can be a
consumer electronics domain that is divided into the subdomains of
televisions, stereo equipment, etc. Documents may correspond to
goods or services.
[0041] The user interface may allow users to navigate in one domain
at a time. Alternatively, the user interface may allow the
simultaneous navigation of multiple domains, particularly when
certain attributes are common to multiple domains.
[0042] The user interface allows the user to navigate through a
collection of navigation states. Each state is composed of a set of
terms and of the set of documents associated with those terms.
Users navigate through the collection of navigation states by
selecting and deselecting terms to obtain the navigation state
corresponding to each set of selected terms. Preferably, as in FIG.
4, the user interface 10 presents a navigation state by displaying
both the list 50 of terms 52 and a list 41 of some or all of the
documents 42 that correspond to that state. Preferably, the user
interface presents the terms 52 of the navigation state organized
by attribute. Preferably, the initial navigation state is a root
state that corresponds to no term selections and, therefore, to all
of the documents in the collection.
[0043] As shown in FIG. 2, the user interface 10 allows users to
narrow the navigation state by choosing a value 28 for an attribute
22, or by replacing the currently selected value with a more
specific one (if appropriate). Preferably, the user interface 10
presents users with the options available to narrow the present
navigation state, preferably with relevant terms organized by
attribute. In some embodiments of the present invention, as shown
in FIG. 2, users can select values 28 from drop-down lists 26
denoted by indicators 24, that are organized by attributes 22 in
the current navigation state. The user interface may present these
navigation options in a variety of formats. For example, values can
be presented as pictures or as symbols rather than as text. The
interface may allow for any method of selecting terms, e.g., mouse
clicks, keyboard strokes, or voice commands. The interface may be
provided through various media and devices, such as television or
WWW, and telephonic or wireless devices. Although discussed herein
primarily as a visual interface, the interface may also include an
audio component or be primarily audio-based.
[0044] Preferably, in the present navigation state, the user
interface only presents options for narrowing the navigation state
that lead to a navigation state with at least one document. This
preferred criteria for providing navigation options ensures that
there are no "dead ends," or navigation states that correspond to
an empty result set.
[0045] Preferably, the user interface only presents options for
narrowing the navigation state if they lead to a navigation state
with strictly fewer documents than the present one. Doing so
ensures that the user interface does not present the user with
choices that are already implied by terms in the current navigation
state.
[0046] Preferably, the user interface presents a new navigation
state as soon as the user has chosen a term 28 to narrow the
current navigation state, without any further triggering action by
the user. Because the system responds to each user with immediate
feedback, the user need not formulate a comprehensive query and
then submit the query.
[0047] In accordance with one embodiment of the present invention,
as shown in FIGS. 3 and 4, the user interface 10 may enable
broadening of the current navigation state by allowing the user to
remove terms 52 from the list 50 of terms selected. For example,
the interface 10 may provide a list 50 with checkboxes 54 for
removing selections and a button 56 to trigger the new search. In
the illustrated embodiment, the user can remove selected terms 52
in any order and can remove more than one selection 52 at a
time.
[0048] Preferably, the navigation options presented to the user are
context-dependent. For example, terms that refine previously
selected terms may become navigation options in the resulting
navigation state. For example, referring to FIG. 5, after the term
Flavors: Wood and Nut Flavors 52 is selected (the user has selected
the value Wood and Nut Flavors 23 for the attribute Flavors), Wood
and Nut Flavors 23 then appears in the interface for the new
navigation state in the list 20 of attributes and allows selection
of values 28 that relate to that specific attribute for further
refinement of the query. The user interface may also present
certain attributes that were not presented initially, as they
become newly relevant. For example, comparing FIG. 3 to FIG. 2, the
attribute French Vineyards 25 appears in the list 20 of attributes
only after the user has already selected the term Regions: French
Regions in a previous navigation state. Attributes may be embedded
in this way to as many levels as are desired. Presenting attributes
as navigation options when those attributes become relevant avoids
overwhelming the user with navigation options before those options
are meaningful.
[0049] Additionally, for some attributes 22, multiple incomparable
(non-refining) selections of values 28 may be applicable. For
example, for the attribute Flavor, the values Fruity and Nutty,
neither of which refines the other, may both be selected so that
the terms Flavors: Fruity and Flavors: Nutty narrow the navigation
state. Thus, users may sometimes be able to refine a query by
selecting multiple values under a single attribute.
[0050] Preferably, certain attributes will be eliminated as
navigation options if they are no longer valid or helpful choices.
For example, if all of the documents in the result set share a
common term (in addition to the term(s) selected to reach the
navigation state), then selection of that term will not further
refine the result set; thus, the attribute associated with that
term is eliminated as a navigation option. For example, comparing
FIG. 6 with FIG. 4, the attribute Wine Types 27 has been eliminated
as a navigation option because all of the documents 42 in the
result set share the same term, Wine Types: Appellational Wines. In
preferred embodiments, an additional feature of the interface 10 is
that this information is presented to the user as a common
characteristic of the documents 42 in the result set. For example,
referring to FIG. 6, the interface 10 includes a display 60 that
indicates the common characteristics of the documents 42 in the
result set. Removing a term as a navigation option when all of the
documents in the result set share that term prevents the user from
wasting time by selecting terms that do not refine the result
set.
[0051] Preferably, the user interface also eliminates values as
navigation options if their selection would result in no documents
in the result set. For example, comparing FIG. 8 to FIG. 7, after
the user selects the term Wine Spectator Range: 95-100, the user
interface eliminates as navigation options all the values 28, 29 in
the list 26 of values for the attribute Appellations 22 except for
the values Alexander Valley 29 and Napa Valley 29. Alexander Valley
29 and Napa Valley 29 are the only two values in the list 26 of
values for the attribute Appellations that return at least one
document in the result set; all other values 28 return the empty
set. Removing values as navigation options that would result in an
empty result set saves the user time by preventing the user from
reaching dead-ends.
[0052] Preferably, the user interface allows users to search for
desired words using free-text search. In accordance with one
embodiment of the present invention, illustrated in FIG. 9, a
search box 30 preferably allows users to perform a free-text search
for terms of interest, rather than performing a full-text search of
the documents themselves. Preferably, the user interface responds
to such a search by presenting a list 32 of terms 34 including
organized by attribute 36, and allowing the user to select from
among them. Preferably, the user interface responds to the user's
selection by presenting the user with the navigation state
corresponding to the selection of that term. The user may then
either navigate from that state (i.e., by narrowing or broadening
it) or perform additional free-text searches for terms.
[0053] Preferably, the user interface 10 presents a full or partial
list 41 of the documents that correspond to the current navigation
state. Preferably, if a user is interested in a particular document
42, the user may select it and obtain a record 70 containing
further information about it, including the list 72 of terms 74
that are associated with that document, as shown in FIG. 10.
Preferably, the user interface 10 allows the user to select any
subset of those terms 74 and thereby navigate to the navigation
state that corresponds to the selected term set.
[0054] Preferably, the user interface 10 also offers navigation
options that directly link to an associated navigation state that
is relevant to, but not necessarily a generalization or refinement
of, the present navigation state. These links preferably infer the
user's interests from the present navigation state and enable the
user to cross-over to a related topic. For example, if the user is
visiting a particular navigation state in a food domain, links may
direct the user to navigation states of wines that would complement
those foods in the wine domain.
[0055] Although the interface to the navigation system has been
described herein as a user interface 10, the interface could
provide other forms of access to the navigation system. In
alternative embodiments, the interface may be an applications
program interface to allow access to the navigation system for or
through other applications. The interface may also enhance the
functionality of an independent data-oriented application. The
interface may also be used in the context of a WWW-based
application or an XML-based application. The navigation system may
also support multiple interface modes simultaneously. The
navigation system may be made available in a variety of ways, for
example via wireless communications or on handheld devices.
[0056] Knowledge Base
[0057] Preferably, the navigation system stores all information
relevant to navigation in a knowledge base. The knowledge base is
the repository of information from two processes: taxonomy
definition and classification. Taxonomy definition is the process
of identifying the relevant attributes to characterize documents,
determining the acceptable values for those attributes (such as a
list or range of values), and defining a partial order of
refinement relationships among terms (attribute-value pairs).
Classification is the process of associating terms with documents.
The knowledge base may also be used to maintain any information
assets that support these two processes, such as domains,
classification rules and default expectations. Additionally, the
knowledge base may be used to maintain supplementary information
and materials that affect users' navigation experience.
[0058] The taxonomy definition process identifies a set of
attributes that appropriately characterize documents. A typical way
to organize the taxonomy definition process is to arrange the
collections of documents into domains, which are sets of documents
that conform to a natural grouping and for which a manageable
number of attributes suffice to effectively distinguish and
navigate among the documents in that domain. The knowledge base
preferably includes a characterization of each domain, which might
include rules or default expectations concerning the classification
of documents in that domain.
[0059] The taxonomy definition process also identifies a full set
of values, at varying levels of specificity when appropriate, for
each attribute. The values preferably identify the specific
properties of the documents in the collection. The values may be
enumerated explicitly or defined implicitly. For example, for a
"color" attribute, a full set of valid color values may be
specified, but for a "price" or "date" attribute, a range within
which the values may fall or a general data type, without defining
a range, may be specified. The process of identifying these values
may include researching the domain or analyzing the collection of
documents.
[0060] The taxonomy definition process also defines a partial order
of refinement relationships among terms (attribute-value pairs).
For example, the term Origin: France could refine the term Origin:
Europe. The refinement relationship is transitive and antisymmetric
but not necessarily total. Transitivity means that, if term A
refines term B and term B refines term C, then term A refines term
C. For example, if Origin: Paris refines Origin: France and Origin:
France refines Origin: Europe, then Origin: Paris refines Origin:
Europe. Antisymmetry means that, if two terms are distinct, then
both terms cannot refine each other. For example, if Origin: Paris
refines Origin: France, then Origin: France does not refine Origin:
Paris.
[0061] Further, the partial order of refinement relationships among
terms is not necessarily a total one. For example, there could be
two terms, Origin: France and Origin: Spain, such that neither term
refines the other. Two terms with this property are said to be
incomparable. Generally, a set of two or more terms is mutually
incomparable if, for every pair of distinct terms chosen from that
set, the two terms are incomparable. Typically, but not
necessarily, two terms with distinct attributes will be
incomparable.
[0062] Given a set of terms, a term is a maximal term in that set
if it does not refine any other terms in the set, and it is a
minimal term in that set if no other term in the set refines it.
For example, in the set {Origin: France, Origin: Paris, Origin:
Spain, Origin: Madrid}, Origin: France and Origin: Spain are
maximal, while Origin: Paris and Origin: Madrid are minimal. In the
knowledge base, a term is a root term if it does not refine any
other terms and a term is a leaf term if no other term refines
it.
[0063] FIGS. 11A, 11B, and 11C illustrate attributes 112 and values
114, arranged in accordance with the partial order relationships,
that could be used for classifying wines. The attributes 112 are
Type/Varietal, Origin, and Vintage. Each attribute 112 corresponds
to a maximal term for that attribute. An attribute 112 can have a
flat set of mutually incomparable values (e.g., Vintage), a tree of
values (e.g., Origin), or a general partial order that allows a
value to refine a set of two or more mutually incomparable values
(e.g., Type/Varietal). The arrows 113 indicate the refinement
relationships among values 114.
[0064] Attributes and values may be identified and developed in
several ways, including manual or automatic processing and the
analysis of documents. Moreover, this kind of analysis may be
top-down or bottom-up; that is, starting from root terms and
working towards leaf terms, or starting from leaf terms and working
towards root terms. Retailers, or others who have an interest in
using the presented invention to disseminate information, may also
define attributes and terms.
[0065] The classification process locates documents in the
collection of navigation states by associating each document with a
set of terms. Each document is associated with a set of mutually
incomparable terms, e.g., {Type/Varietal: Chianti, Origin: Italy,
Vintage: 1996}, as well as any other desired descriptive
information. If a document is associated with a given term, then
the document is also associated with all of the terms that the
given term refines.
[0066] The classification process may proceed according to a
variety of workflows. Documents may be classified in series or in
parallel, and the automatic and manual classification steps may be
performed one or more times and in any order. To improve accuracy
and throughput, human experts may be assigned as specialists to
oversee the classification task for particular subsets of the
documents, or even particular attributes for particular subsets of
the documents. In addition, the classification and taxonomy
processes may be interleaved, especially as knowledge gained from
one process allows improvements in the other.
[0067] FIG. 12 illustrates the stages in a possible flow for the
classification process 250. The data acquisition step 252, that is,
the collection of documents for the database, may occur in several
different ways. For example, a retailer with a product catalog over
which the navigation system will operate might provide a set of
documents describing its products as a pre-defined set.
Alternatively, documents may be collected from one source, e.g.,
one Web site, or from a number of sources, e.g., multiple Web
sites, and then aggregated. If the desired documents are Web pages,
the documents may be collected by appropriately crawling the Web,
selecting documents, and discarding documents that do not fit in
the domain. In the data translation step 254, the collected
documents are formatted and parsed to facilitate further
processing. In the automatic classification step 256, the formatted
and parsed documents are processed in order to automatically
associate documents with terms. In the manual classification step
258, human reviewers may verify and amend the automatic
classifications, thereby ensuring quality control. Preferably, any
rules or expectations violated in either the automatic
classification step 256 or the manual classification step 258 would
be flagged and presented to human reviewers as part of the manual
classification step 258. If the collection of documents is divided
into domains, then there will typically be rules that specify a
certain minimal or preferred set of attributes used to classify
documents from each domain, as well as other domain-specific
classification rules. When the classification process is complete,
each document will have a set of terms associated with it, which
locate the document in the collection of navigation states.
[0068] In FIG. 13, table 180 shows a possible representation of a
collection of classified wine bottles. Preferably, each entry is
associated with a document number 182, which could be a universal
identifier, a name 184, and the associated terms 186. The name is
preferably descriptive information that could allow the collection
to be accessed via a free-text search engine as well as via the
term-based navigation system.
[0069] In another aspect of the invention, the knowledge base also
includes a catalog of canonical representations of documents. Each
catalog entry represents a conceptually distinct item that may be
associated with one or more documents. The catalog allows
aggregation of profile information from multiple documents that
relate to the item, possibly from multiple sources. For example, if
the same wine is sold by two vendors, and if one vendor provides
vintage and geographic location information and another provides
taste information, that information from the two vendors can be
combined in the catalog entry for that type of wine. The catalog
may also improve the efficiency of the classification process by
eliminating duplicative profiling. In FIG. 12, the catalog creation
step 260 associates classified documents with catalog entries,
creating new catalog entries when appropriate. For ease of
reference, an item may be uniquely identified in the catalog by a
universal identifier.
[0070] The knowledge base may also define stores, where a store is
a subcollection of documents that are grouped to be searchable at
one time. For example, a particular online wine merchant may not
wish to display documents corresponding to products sold by that
merchant's competitors, even though the knowledge base may contain
such documents. In this case, the knowledge base can define a store
of documents that does not include wines sold by the merchant's
competitors. In FIG. 12, the store creation step 262 may define
stores based on attributes, terms, or any other properties of
documents. A document may be identified with more than one store.
The knowledge base may also contain attributes or terms that have
been customized for particular stores.
[0071] In FIG. 12, the export process step 264 exports information
from the knowledge base to another stage in the system that
performs further processing necessary to generate a navigable data
structure.
[0072] Navigation States
[0073] The navigation system represents, explicitly or implicitly,
a collection of navigation states. These navigation states are
related by a partial order of refinement that is derived from the
partial order that relates the terms.
[0074] A navigation state has two representations. First, a
navigation state corresponds to a subset of the collection of
documents. Second, a navigation state corresponds to a set of
mutually incomparable terms. FIG. 14 illustrates some navigation
states for the documents and terms based on the wine example
discussed above. For example, one navigation state 224 is {Origin:
South America} (documents #1, #4, #5); a second navigation state
224 is {Type/Varietal: White, Origin: United States} (documents #2,
#9). The subset of documents corresponding to each navigation state
includes the documents that are commonly associated with all of the
terms in the corresponding set of mutually incomparable terms. At
the same time, the set of mutually incomparable terms corresponding
to each navigation state includes all of the minimal terms from the
set of terms that are common to the subset of documents, i.e., the
set of terms that are commonly associated with every document in
the subset. Each navigation state is preferably unique and fully
specified; for a particular set of terms, or for a given set of
documents, there is no more than one corresponding navigation
state.
[0075] One way preferred to define the collection of navigation
states is to uniquely identify each navigation state by a canonical
set of mutually incomparable terms. A two-step mapping process that
maps an arbitrary term set to a canonical set of mutually
incomparable terms creates states that satisfy this property. In
the first step of the process, an arbitrary set of terms is mapped
to the subset of documents that are associated with all of those
terms. Recalling that if a document is associated with a given
term, then the document is also associated with all of the terms
that the given term refines, in the second step of the process,
this subset of documents is mapped to the set of minimal terms in
the set of terms that are common to all of the documents in that
document set. The term set derived from this second step is a set
of mutually incomparable terms that uniquely identifies the
corresponding subset of documents, and, hence, is a canonical
representation for a navigation state. By way of illustration,
referring to the wine example in FIG. 14, the term set {Origin:
France} maps to the subset of documents {documents #8, #11}, which
in turn maps to the canonical term set {Type/Varietal: Red, Origin:
France}.
[0076] The navigation states 222, 224, 226 are related by a partial
order of refinement relationships 220 derived from the partial
order that relates terms. This partial order can be expressed in
terms of either the subsets of documents or the term sets that
define a navigation state. Expressed in terms of subsets of
documents, a navigation state A refines a navigation state B if the
set of documents that corresponds to state A is a subset of the set
of documents that corresponds to state B. Expressed in terms of
term sets, a navigation state A refines a navigation state B if all
of the terms in state B either are in state A or are refined by
terms in state A. Referring to FIG. 14, the navigation state 226
corresponding to the term set {Type/Varietal: Red, Origin: Chile}
(document #4) refines the navigation state 224 corresponding to
{Origin: Chile} (documents #4, #5). Since the refinement
relationships among navigation states give rise to a partial order,
they are transitive and antisymmetric. In the example,
{Type/Varietal: Red, Origin: Chile} (document #4) refines {Origin:
Chile} (documents #4, #5) and {Origin: Chile} (documents #4, #5)
refines {Origin: South America} (documents #1, #4, #5); therefore,
{Type/Varietal: Red, Origin: Chile} (document #4) refines {Origin:
South America} (documents #1, #4, #5). The root navigation state
222 is defined to be the navigation state corresponding to the
entire collection of documents. The leaf navigation states 226 are
defined to be those that cannot be further refined, and often
(though not necessarily) correspond to individual documents. There
can be arbitrarily many intermediate navigation states 224 between
the root 222 and the leaves 226. Given a pair of navigation states
A and B where B refines A, there can be multiple paths of
intermediate navigation states 224 connecting A to B in the partial
order. For convenience of definition in reference to the
implementation described herein, a navigation state is considered
to refine itself.
[0077] A user browses the collection of documents by visiting a
sequence of one or more navigation states typically starting at the
root navigation state 222. There are three basic modes of
navigation among these states. The first mode is refinement, or
moving from the current navigation state to a navigation state that
refines it. The user can perform refinement either by adding a term
to the current navigation state or by refining a term in the
current navigation state; i.e., replacing a term with a refinement
of that term. After the user adds or refines a term, the new term
set can be mapped to a canonical term set according to the two-step
mapping described above. The second mode is generalization, or
moving from the current navigation state to a more general
navigation state that the current state refines. The user can
perform generalization either by removing a term from the current
navigation state or by generalizing a term in the current
navigation state; i.e., replacing a current term with a term that
the current term refines. After the user removes or generalizes a
term, the new term set can be mapped to a canonical term set. The
third mode is simply creating a query in the form of a desired term
set, which again can be mapped to a canonical term set to obtain a
navigation state.
[0078] Implementation
[0079] The knowledge base is transferred to a navigable data
structure in order to implement the present invention. The
navigation states may be fully precomputed, computed dynamically at
run-time, or partially precomputed. A cache may be used to avoid
redundant computation of navigation states.
[0080] In preferred embodiments, the collection of navigation
states may be represented as a graph--preferably, a directed
acyclic multigraph with labeled edges. A graph is a combinatorial
structure consisting of nodes and edges, where each edge links a
pair of nodes. The two nodes linked by an edge are called its
endpoints. With respect to the present invention, the nodes
correspond to navigation states, and the edges represent
transitions that refine from one navigation state to another. Since
refinement is directional, each edge is directed from the more
general node to the node that refines it. Because there is a
partial order on the navigation states, there can be no directed
cycles in the graph, i.e., the graph is acyclic. Preferably, the
graph is a multigraph, since it allows the possibility of multiple
edges connecting a given pair of nodes. Each edge is labeled with a
term. Each edge has the property that starting with the term set of
the more general end point, adding the edge term, and using the
two-step map to put this term set into canonical form leads to a
refinement which results in the navigation state that is the other
endpoint. That is, each edge represents a refinement transition
between nodes based on the addition of a single term.
[0081] The following definitions are useful for understanding the
structure of the graph: descendant, ancestor, least common ancestor
(LCA), proper ancestor, proper descendant, and greatest lower bound
(GLB). These definitions apply to the refinement partial order
among terms and among nodes. If A and B are terms and B refines A,
then B is said to be a descendant of A and A is said to be an
ancestor of B. If, furthermore, A and B are distinct terms, then B
is said to be a proper descendant of A and A is said to be a proper
ancestor of B. The same definitions apply if A and B are both
nodes.
[0082] If C is an ancestor of A and C is also an ancestor of B,
then C is said to be a common ancestor of A and B, where A, B, and
C are either all terms or all nodes. The minimal elements of the
set of common ancestors of A and B are called the least common
ancestors (LCAs) of A and B. If no term has a pair of incomparable
ancestors, then the LCA of two terms--or of two nodes--is unique.
For example, the LCA of Origin: Argentina and Origin: Chile is
Origin: South America in the partial order of terms 110 of FIG.
11B. In general, however, there may be a set of LCAs for a given
pair of terms or nodes.
[0083] Computation of the nodes in the graphs is preferably
performed bottom-up.
[0084] The leaf nodes in the graph--that is, the nodes
corresponding to leaf navigation states--may be computed directly
from the classified documents. Typically, but not necessarily, a
leaf node will correspond to a set containing a single document.
The remaining, non-leaf nodes are obtained by computing the
LCA-closure of the leaf nodes--that is, all of the nodes that are
the LCAs of subsets of the leaf nodes.
[0085] The edges of the graph are determined according to a
refinement function, called the R function for notational
convenience. The R function takes as arguments two nodes A and B,
where A is a proper ancestor of B, and returns the set of maximal
terms such that, if term C is in R (A, B), then refining node A
with term C results in a node that is a proper descendant of A and
an ancestor (not necessarily proper) of B. For example, in FIG. 14,
R ({Type/Varietal: Red}, {Type/Varietal: Merlot, Origin: Argentina,
Vintage: 1998})={Type/Varietal: Merlot, Origin: South America,
Vintage: 1998}. If B is an ancestor of B.sub.2, then R (A, B.sub.1)
is a subset of R (A, B.sub.2)--assuming that A is a proper ancestor
of both B.sub.1 and B.sub.2. For example, R ({Type/Varietal: Red},
{Type/Varietal: Red, Origin: South America})={Origin: South
America}.
[0086] In the graph, the edges between nodes A and B will
correspond to a subset of the terms in R (A, B). Also, no two edges
from a single ancestor node A use the same term for refinement. If
node A has a collection of descendant nodes {B.sub.1, B.sub.2, . .
. } such that term C is in all of the R (A, B.sub.i), then the only
edge from node A with term C goes to LCA (B.sub.1, B.sub.2, . . .
), which is guaranteed to be the unique maximal node among the
B.sub.i. In FIG. 14, for example, the edge from node
{Type/Varietal: Red} with term Origin: South America goes to node
{Type/Varietal: Red, Origin: South America} rather than to that
node's proper descendants {Type/Varietal: Merlot, Origin: South
America, Vintage: 1998} and {Type/Varietal: Red, Origin: Chile}.
The LCA-closure property of the graph ensures the existence of a
unique maximal node among the B.sub.i. Thus, each edge maps a
node-term pair uniquely to a proper descendant of that node.
[0087] The LCA-closure of the graph results in the useful property
that, for a given term set S, the set of nodes whose term sets
refine S has a unique maximal node. This node is called the
greatest lower bound (GLB) of S.
[0088] The graph may be computed explicitly and stored in a
combinatorial data structure; it may be represented implicitly in a
structure that does not necessarily contain explicit
representations of the nodes and edges; or it may be represented
using a method that combines these strategies. Because the
navigation system will typically operate on a large collection of
documents, it is preferred that the graph be represented by a
method that is scalable.
[0089] The graph could be obtained by computing the LCAs of every
possible subset of leaf nodes. Such an approach, however, grows
exponentially in the number of leaf nodes, and is inherently not
scalable. An alternative strategy for obtaining the LCA closure is
to repeatedly consider all pairs of nodes in the graph, check if
each pair's LCA is in the graph, and add that LCA to the graph as
needed. This strategy, though a significant improvement on the
previous one, is still relatively not scalable.
[0090] A more efficient way to precompute the nodes is to process
the document set sequentially, compute the node for each document,
and add that node to the graph along with any other nodes necessary
to maintain LCA-closure. The system stores the nodes and edges as a
directed acyclic multigraph. The graph is initialized to contain a
single node corresponding to the empty term set, the root node.
Referring to FIG. 15, in process 230 for inserting a new node into
the graph, in step 232, for each new document to be inserted into
the graph that does not correspond to an existing node, the system
creates a new node. In step 234, before inserting the new node into
the graph, the system recursively generates and inserts any missing
LCA nodes between the root node (or ancestor node) and the new
node. To ensure LCA-closure after every node insertion, the system
inserts the document node last, in steps 236 and 238, after
inserting all the other nodes that are proper ancestors of it.
[0091] Inserting a new node requires the addition of the
appropriate edges from ancestors to the node, in step 236, and to
descendants out of the new node, in step 238. The edges into the
node are preferably determined by identifying the ancestors that
have refinement terms that lead into the new node and do not
already have those refinement terms used on edges leading to
intermediate ancestors of the new node. The edges out of the node
are preferably determined by computing the GLB of the new node and
appropriately adding edges from the new node to the GLB and to
nodes to which the GLB has edges.
[0092] The entire graph may be precomputed by following the above
procedures for each document in the collection. Precomputing of the
graph may be preferred where the size of the graph is manageable,
or if users are likely to visit every navigation state with equal
probability. In practice, however, users typically visit some
navigation states more frequently than others. Indeed, as the graph
gets larger, some navigation states may never be visited at all.
Unfortunately, reliable predictions of the frequency with which
navigation states will be visited are difficult.
[0093] An alternative strategy to precomputing the navigation
states is to create indexes that allow the navigation states to be
computed dynamically. Specifically, each document can be indexed by
all of the terms that are associated with that document or that
have refinements associated with that document. The resulting index
is generally much smaller in size than a data structure that stores
the graph of navigation states. This dynamic approach may save
space and precomputation time, but it may do so at the cost of
higher response times or greater computational requirements for
operation. A dynamic implementation may use a one-argument version
of the R function that returns all refinement terms from a given
navigation state, as well a procedure for computing the GLB of a
term set.
[0094] It is also possible to precompute a subset of the navigation
states. It is preferable to precompute the states that will cost
the most to compute dynamically. For example, if a state
corresponds to a large subset of the documents, it may be
preferable to compute it in advance. In one possible partial
precomputation approach, all navigation states corresponding to a
subset of documents above a threshold size may be precomputed.
Precomputing a state is also preferable if the state will be
visited frequently. In some instances it may be possible to predict
the frequency with which a navigation state will be visited. Even
if the frequency with which a navigation state will be visited
cannot be predicted in advance, the need to continually recompute
can be reduced by caching the results of dynamic computation. Most
recently or most frequently visited states may be cached.
[0095] As described above with respect to the interface, the system
supports three kinds of query operations--namely refinement,
generalization, and query by specifying a set of terms. These
operations may be further described in terms of the graph. For
query refinement, the system enumerates the terms that are on edges
from the node corresponding to the current navigation state. When
the user selects a term for refinement, the system responds by
presenting the node to which that edge leads. Similarly, for query
generalization options, the system enumerates and selects edges
that lead to (rather than from) the node corresponding to the
current navigation state. Alternatively, query generalization may
be implemented as a special case of query by specifying a set of
terms. For query by specifying a set of keywords, the system
creates a virtual node corresponding to the given term set and
determines the GLB of the virtual node in the graph. If no GLB is
found, then there are no documents that satisfy the query.
Otherwise, the GLB node will be the most general node in the graph
that corresponds to a navigation state where all documents satisfy
the query.
[0096] The navigation system of the present invention allows
information providers to overlay a navigation system over any
collection of documents. The knowledge base and navigation aspects
of the invention can be performed independently by different
providers, and information providers may outsource these functions
to separate entities. Similarly, a generated knowledge base may be
imported by a navigation specialist. Information providers may also
outsource this navigation requirement to a navigation system
provider. A navigation system provider could charge customers a
license fee for the system independent of the amount of its usage.
Alternatively, a navigation system provider could charge customers
on a per-click basis, a per-purchase basis if products are
available via the system, or per-transaction generated from a click
through the navigation system. A navigation system provider could
also function as an aggregator--compiling records from a number of
sources, combining them into a global data set, and generating a
navigation system to search the data set.
[0097] A navigation system in accordance with the present invention
may also enhance user profiling capability and merchandising
capability. The navigation system may maintain a profile of users
based on the users' selections, including the particular paths
selected to explore the collection of navigation states. Using the
knowledge base, the system may also infer additional information
regarding the users' preferences and interests by supplementing the
selection information with information regarding related documents,
attributes and terms in the knowledge base. That information may be
used to market goods and services related to the documents of
interest to the user.
[0098] The foregoing description has been directed to specific
embodiments of the invention. The invention may be embodied in
other specific forms without departing from the spirit and scope of
the invention. The embodiments, figures, terms and examples used
herein are intended by way of reference and illustration only and
not by way of limitation. The scope of the invention is indicated
by the appended claims and all changes that come within the meaning
and scope of equivalency of the claims are intended to be embraced
therein.
* * * * *