System and method for implementing a knowledge management system

• US 7,401,087 B2
• Filed: 07/01/2003
• Issued: 07/15/2008
• Est. Priority Date: 06/15/1999
• Status: Expired due to Term

• Current Assignee: Avolin LLC
• Original Assignee: Consona CRM Incorporated (Aptean Superior Holdings, Inc.)
• Inventors: Kay, David B., Copperman, Max, Huffman, Scott B., Fratkina, Raya, Angel, Mark, Rudy, Jeffrey H.
• Primary Examiner(s): Al-Hashemi; Sana
• Application Number:
  US10/610,994
• Publication Number:
  US 20040024739A1
• Time in Patent Office: 1,841 Days
• Field of Search: 707101-103 R
• US Class Current: 707/737
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G06F 16/3338 Query expansion
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99944 Object-oriented database structure
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing
• CPC Class Codes: Y10S 707/99948 Application of database or data structure, e.g. distributed, multimedia, or image

Abstract

A method and system organize and retrieve information using taxonomies, a document classifier, and an autocontextualizer. Documents (or other knowledge containers) in an organization and retrieval subsystem may be manually or automatically classified into taxonomies. Documents are transformed from clear text into a structured record. Automatically constructed indexes help identify when the structured record is an appropriate response to a query. An automatic term extractor creates a list of terms indicative of the documents'"'"' subject matter. A subject matter expert identifies the terms relevant to the taxonomies. A term analysis system assigns the relevant terms to one or more taxonomies, and a suitable algorithm is then used to determine the relatedness between each list of terms and its associated taxonomy. The system then clusters documents for each taxonomy in accordance with the weights ascribed to the terms in the taxonomy'"'"'s list and a directed acyclic graph (DAG) structure is created.

Claims

1. A method of processing a query to identify a particular knowledge container, associated with a knowledge map, that is relevant to the query, wherein the knowledge map includes at least one taxonomy representing a discrete perspective of a knowledge domain, wherein the at least one taxonomy is organized into a group of nodes, the nodes representing conceptual areas within the discrete perspective, and wherein the nodes have an indication of knowledge, including the particular content associated therewith, said method comprising the steps of:

(a) processing at least one of (i) the query to identify nodes of the taxonomies within the knowledge map that are potentially relevant conceptual areas; and

(ii) information about a user to identify nodes in the taxonomy that represent conceptual areas previously indicated to be of interest to the user;

(b) identifying knowledge map regions surrounding at least one of the identified nodes;

(c) performing a content-based retrieval over the knowledge containers associated with the nodes in each identified region, to retrieve an ordered list of potentially relevant knowledge containers, where each retrieved knowledge container is assigned a numerical relevance score representing a quality of association between the retrieved knowledge container and the query; and

(d) returning as a result the ordered list of the knowledge containers.

2. The method of claim 1, further including the step of returning the potentially relevant nodes and knowledge map regions.

3. The method of claim 1, wherein the content based retrieval step operates upon one content-based search engine index for all knowledge containers associated with nodes of the knowledge map.

4. The method of claim 1, in which the content-based retrieval step operates on at least one distinct content-based search engine index per region, where each index indexes or points to a subset of the knowledge containers associated with nodes of the knowledge map.

5. The method of claim 1, wherein the content-based retrieval step is performed over a group of indexes for each knowledge map region, wherein the group of indexes for a particular region is based on indexes for nodes in that knowledge-map.

6. The method of claim 1, wherein the query processing step further includes the step of augmenting the set of identified nodes with additional nodes as input to the query process.

7. The method of claim 1, comprising combining the ordered lists for the identified regions into a single re-ordered list, based on calculating the quality of associations between the knowledge container in the list, the knowledge map, and the query. wherein the list combining step includes the following steps:

modifying the numeric relevance scores; and

combining the ordered lists into the single reordered list based on the modified relevance scores;

wherein the numeric relevance score for a knowledge container in a particular knowledge map region is modified at least partially based on a quality measure for that knowledge map region.

8. The method of claim 1, wherein the query includes taxonomic restrictions limiting the areas of the knowledge map from which a knowledge container is returned in response to the query.

9. The method of claim 1, further including a step of processing administrative meta-data constraints to limit the knowledge containers included in the result, the administrative meta-data constraints including at least one of:

names of authors of the knowledge containers;

date ranges for creation date of the knowledge containers;

date ranges for last modified date of the knowledge containers;

date ranges for expiration date of the knowledge containers;

words or phrases which must be present in the title of the knowledge containers;

name of publication or source in which the knowledge containers originally appeared; and

name of customers for which the knowledge containers were originally prepared.

10. The method of claim 1, further including the following steps:

receiving input from a user as to the suitability of particular portions of the returned result;

modifying the query in response to the input; and

repeating steps (a)–

(d), using the modified query.

11. The method of claim 1, further comprising the step of generating clarifying questions based on the nodes for potentially relevant knowledge containers, wherein the input is provided at least partially in response to answers from a user to the clarifying questions.

12. The retrieval method of claim 1, further comprising the step of generating suggested additional terms for the query based on the nodes for potentially relevant knowledge containers, wherein the query is modified in response to a user choosing from the additional terms.

13. The retrieval method of claim 1, further comprising the steps of:

generating parameterized questions from which a user can interactively construct a taxonomic restriction to limit the areas of the knowledge map or construct a query from which result knowledge content is returned in response to the query, said parameterized questions including;

a boolean taxonomy-restriction expression, where the concept nodes in the expression are replaced with variables;

text of a previously composed question comprised of a plurality of text selection-list boxes for each variable within the boolean taxonomy-restriction expressiun, wherein each selection-list box holds lists of names or descriptions of concept-nodes that are potential values for the variable;

said lists being assembled using the names or descriptions of concept-nodes returned by the retrieval mechanism in the previous step of the dialog, possibly augmented with other nearby concept-nodes from the same taxonomies;

said selection-list boxes optionally having pre-selected as the default choice for the user the specific concept-nodes returned by the retrieval mechanism in the previous step of the dialog, such that when a user selects concept-nodes for each selection-list box within the parameterized question, the boolean taxonomy-restriction expression is instantiated by replacing each of its variables with the corresponding selection-list box selection, and the resulting taxonomic restriction is added to the user s query for the subsequent step of the dialog.

14. The method of claim 1, wherein the knowledge container includes other intellectual content or an indication of a person who has knowledge contact is associated.

15. The retrieval method of claim 1, wherein:

some of the content associated with the nodes of the knowledge map include an indication of a user and the user'"'"'s interests; and

at least some of the steps of the retrieval process account for the user'"'"'s interests.

16. The knowledge retrieval process of claim 1, wherein the process is initiated from a user application, and combining the ordered lists for the identified regions into a single re-ordered list, based on calculating the quality of associations between the knowledge container in the list, the knowledge map, and the query, wherein the list combining step operates based on information about the user application.

17. The knowledge retrieval process of claim 1, comprising combining the ordered lists for the identified regions into a single re-ordered list, based on calculating the quality of associations between the knowledge container in the list, the knowledge map, and the query, wherein the list combining step operates at least in part based on an identification of nodes of the knowledge map by a user.

18. The method of claim 1, wherein the performing the content-based retrieval includes using a knowledge container including:

an indication of an object; and

at least one tag, wherein each tag associates the object to a knowledge map representation of a discrete perspective of a domain of knowledge.

19. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container, wherein the knowledge container is represented by a markup language such that it is displayable using template-based automated processing.

20. The method of claim 1, comprising processing at least one tag to generate a summary of a knowledge container, comprising the steps of:

generating a natural language template based on at least one tag stored inside the knowledge container; and

merging content from the knowledge container and the tagged concept-nodes into the template.

21. The method of claim 1, comprising:

combining the ordered lists for the identified regions into a single re-ordered list, based on calculating the quality of associations between the knowledge container in the list, the knowledge map, and the query; and

returning as a result the re-ordered list of the retrieved knowledge containers.

22. The method of claim 4, wherein for each concept node in at least some of the taxonomies, the knowledge containers whose content is associated with those nodes are indexed by a distinct index.

23. The method of claim 4, wherein in the subset of knowledge containers in each index have similarity of vocabulary.

24. The method of claim 4, wherein the content-based retrieval step further includes:

performing an additional search over an index for all knowledge containers associated with concept nodes in the knowledge map.

25. The retrieval method of claim 6, wherein the method is initiated from a user application, and wherein information about the user application is provided in the form of concept nodes added to the query.

26. The method of claim 7, wherein the quality measure for a particular knowledge-map region is derived from a quality measure for each of the potentially relevant concept nodes around which the knowledge-map region surrounds.

27. The method of claim 7, wherein the numeric relevance score for a particular knowledge container is adjusted based on a quality measure for that knowledge container.

28. The method of claim 7, wherein the quality measure for a particular knowledge container is based on weights of association of the knowledge container with nodes of the taxonomies.

29. The method of claim 7, wherein the quality measure for a particular knowledge container is based at least in part by how many knowledge map regions with which the knowledge container has associated nodes.

30. The methods of claim 7, wherein the quality measure for a particular knowledge container is dependent on a taxonomic distance between the nodes in the knowledge map with which the knowledge container is associated and nodes in the knowledge map with which the query is associated.

31. The method of claim 7, wherein the query is a present query, and wherein the quality measure for a particular knowledge container is based at least in part on a previously-determined overall quality score for the knowledge container based on from users presented with the knowledge container in response to previous queries.

32. The method of claim 8, wherein the taxonomic restrictions include:

a) a restriction that all knowledge containers returned must be associated with nodes in a particular one or more of the taxonomies;

b) a restriction that all knowledge containers returned must be associated with particular nodes;

c) a restrictions that all knowledge containers returned must be associated with nodes either at or taxonomically under a particular node or nodes; and

d) a boolean combination of the restrictions a), b) and c).

33. The retrieval method of claim 15, wherein the steps that account for the user'"'"'s interests include combining the ordered lists for the identified regions into a single re-ordered list, based on calculating the quality of associations between the knowledge container in the list, the knowledge map, and the query.

34. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container wherein the object is one of content and resources.

35. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container including administrative meta-data, comprised of structured information about the object.

36. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container wherein the indication of the object is the object itself.

37. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container wherein the indication of the object is a pointer to the object.

38. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container including:

marked content that is a textual representation of the object;

selective demarcation of regions of the textual representation of the object; and

a plurality of indicators of the nature of the content.

39. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container wherein each tag includes a weight indication representing a strength of association of the knowledge container to a particular node.

40. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container wherein said at least one tag is associated with nodes from a single taxonomy.

41. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container wherein said at least one tag is associated with nodes from a plurality of taxonomies.

42. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container wherein the object indicates a person'"'"'s interests, information needs, and entitlements.

43. The method of claim 42, wherein the performing the content-based retrieval includes using a knowledge container, wherein the person'"'"'s entitlements are represented as tags to nodes of an entitlement taxonomy.

44. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container, wherein the tags for the knowledge container include a weight representing:

a strength of the person'"'"'s interest or information need;

relevancy to a question; and

expertise of a provider.

45. The method of claim 18, wherein the performing the content-based retrieval includes using a knowledge container, wherein the tags for the knowledge container associate the knowledge container with various portions of the knowledge map.

46. The method of claim 1, comprising processing information about a user to identify nodes in the taxonomy that represent conceptual areas previously indicated to be of interest to a user.

47. The method of claim 46, wherein the indication of the user'"'"'s interests and information needs includes a query for use by a retrieval method to retrieve objects mapped to the knowledge map.

48. The method of claim 23, wherein the subsets of knowledge containers in each index are formed by steps of:

aggregating the content indicated by knowledge containers associated with each node into a single block of content;

grouping the blocks together based on vocabulary occurring within the blocks, using a text clustering system; and

grouping those knowledge containers whose content comprises the forming the knowledge containers from which the blocks in a group originate into a distinct subset.

49. The method of claim 26, wherein the quality measure for a potentially relevant concept node is based on the weight value determined in the query process step when identifying a node for a potentially relevant conceptual area.

50. The method of claim 26, wherein the quality measure for a node for a potentially relevant conceptual area is based on a weight for that node determined in the query process step.

51. The method of claim 32, where said taxonomic restrictions further include a restriction that all knowledge containers returned must be tagged to concept-nodes either at or within a particular taxonomic distance of a particular concept-node or nodes.

52. The method of claim 32, where said taxonomic restrictions further include:

a) a restriction that all knowledge containers returned may not be associated with nodes in a particular one or more of the taxonomies;

b) a restriction that all knowledge containers returned may not be associated with particular nodes;

c) a restrictions that all knowledge containers returned may not be associated with nodes either at or taxonomically under a particular node or nodes; and

d) a boolean combination of the restrictions a), b) and c).

53. The retrieval method of claim 33, wherein the numerical relevance scores are modified based on a correlation between the user s interests and the nodes with which the retrieved knowledge container is associated.

54. The method of claim 35, wherein the performing the content-based retrieval includes using a knowledge container wherein the administrative metadata contains a description of the method used to assign the knowledge container to a particular node, including:

SME designation;

autocontextualization;

source mapping based on where the knowledge container came from; and

dialog response.

55. The method of claim 51, further including the step of constructing the taxonomic restrictions.

56. The method of claim 51, wherein said constructing step is further comprised of the step of manually interacting with a graphical display of the knowledge map to indicate desired taxonomic restrictions.

57. The method of claim 51, wherein the interfacing step includes the step of receiving a textual query from the user.

58. The method of claim 51, wherein indications of knowledge experts are associated with nodes for which the conceptual areas represented by the nodes are with the expert'"'"'s area of expertise, and

wherein information about the experts may be included as part of the result of processing the query.

59. The retrieval method of claim 56, wherein the process is initiated from a user application, and wherein information about the user application is provided as the taxonomic restrictions.

60. The method of claim 46, combining the ordered lists for the identified regions into a single re-ordered list, based on calculating the quality of associations between the knowledge container in the list, the knowledge map, and the query, wherein the information about the customer is processed automatically with any action by the user, and wherein at least one portion of the knowledge container of the re-ordered list is displayed to the user.