System and method for implementing a knowledge management system
DCFirst Claim
1. A knowledge map representation of selected discrete perspectives of a domain of knowledge, said knowledge map useable by a knowledge instance classification computer program to classify instances of knowledge according to said discrete perspectives, said representation comprising:
- a plurality of separate taxonomies, each separate taxonomy representing one of said discrete perspectives of the knowledge domain;
wherein each taxonomy is organized as a graph of nodes, connected by edges, each node of said graph corresponding to a conceptual area within the discrete perspective that the taxonomy represents and each edge of said graph representing a parent-child relationship between the conceptual areas to which the nodes connected to that edge correspond.
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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 terns 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.
885 Citations
34 Claims
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1. A knowledge map representation of selected discrete perspectives of a domain of knowledge, said knowledge map useable by a knowledge instance classification computer program to classify instances of knowledge according to said discrete perspectives, said representation comprising:
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a plurality of separate taxonomies, each separate taxonomy representing one of said discrete perspectives of the knowledge domain;
wherein each taxonomy is organized as a graph of nodes, connected by edges, each node of said graph corresponding to a conceptual area within the discrete perspective that the taxonomy represents and each edge of said graph representing a parent-child relationship between the conceptual areas to which the nodes connected to that edge correspond.
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2. The knowledge map of claim 1, wherein said graph is a directed acyclic graph.
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3. The knowledge map of claim 1, wherein said graph is a hierarchical graph.
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4. The knowledge map representation of claim 1, further comprising at least one knowledge instance associated with at least one node of said taxonomies;
wherein the at least one association includes a classification of the knowledge instance within the knowledge domain.
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5. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises a topic taxonomy, in which each node of the topic taxonomy represents one or more topics and an association of a knowledge instance with a node of said topic taxonomy indicates that at least some content of the knowledge instance is about the topic represented by that node.
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6. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises a process taxonomy, in which each node of the process taxonomy represents a step in one or more business processes, and an association of a knowledge instance with a node of said process taxonomy indicates that at least some content of the knowledge instance is pertinent to the step represented by the node.
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7. A knowledge map representation as in claim 6, wherein the at least one entity is a person, place, organization, product, family of products, or a customer segment.
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8. The knowledge map representation of claim 1, wherein a taxonomic distance function between nodes is associated with at least one pair of nodes of a taxonomy and is a function of the graphical representation of the taxonomy.
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9. The knowledge map representation of claim 8, wherein the at least one pair of nodes includes a parent node and a child node, and wherein the taxonomic distance function for the pair of nodes in the direction from the parent node to the child node is different than for the direction from the child node to the parent node.
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10. The knowledge map representation of claim 8, wherein the taxonomic distance function for the at least one pair of nodes of a taxonomy at least partially depends on how deep in the taxonomy is the pair of nodes.
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11. The knowledge map representation of claim 8, wherein the taxonomic distance function includes one or more parameters incorporated manually by a human user, wherein the taxonomic distance function accounts for human knowledge about a semantic distance between nodes in the taxonomy.
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12. The knowledge map representation of claim 11, wherein the manually incorporated one or more parameters are represented in an editable table to facilitate computing the taxonomic distance function for a particular pair of nodes.
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13. The knowledge map representation of claim 8, wherein the taxonomic distance function for a pair of nodes of a taxonomy at least partially depends on a type of that taxonomy.
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14. The knowledge map representation of claim 1, wherein the knowledge map includes a plurality of knowledge map regions, wherein each knowledge map region comprises a group of one or more nodes collectively representing a coherent subdomain of knowledge.
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15. The knowledge map representation of claim 14, wherein all nodes in a particular knowledge map region are in the same taxonomy.
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16. The knowledge map representation of claim 15, wherein:
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taxonomic distance between nodes is a function of the graphical representation into which the taxonomy is organized;
the knowledge map region is generally centered about a particular central node; and
the nodes that are members of the region are those nodes having a lower taxonomic distance from the particular central node than nodes that are not members of the region associated with the particular central node.
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17. The knowledge map representation of claim 15, wherein:
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one or more knowledge containers are associated with at least some of the nodes; and
the nodes that are a member of the region have a similarity of vocabulary in the content of their associated knowledge containers.
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18. The knowledge map representation of claim 15, wherein:
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the knowledge map region is generally centered about a particular central node;
one or more knowledge containers are associated with at least some of the nodes; and
the nodes that are members of the region are (1) those nodes having less taxonomic distance from the particular central node than nodes that are not members of the region, and also (2) for which there is similar vocabulary in the content of their. associated knowledge containers.
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19. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises a filter taxonomy, in which each node of the filter taxonomy represents meta-data, which are characteristics of knowledge instances that cannot be readily derived from the content of the knowledge instance, and an association of a knowledge instance with a node of said filter taxonomy indicates that the knowledge instance includes the characteristic represented by that node.
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20. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises a lexical taxonomy, in which each node of the lexical taxonomy represents a concept in the knowledge domain that is identifiable by one or more specific words or phrases, and an association of a knowledge instance with a node of said lexical taxonomy indicates that the knowledge instance includes one or more instances of the words or phrases indicative of the concept represented by that node.
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21. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises an environment taxonomy, in which each node of the environment taxonomy represents at least one entity.
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22. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises a diagnostic taxonomy, in which each node of the diagnostic taxonomy represents at least one symptom of a problem, and an association of a knowledge instance with a node of said diagnostic taxonomy indicates that at least some content of the knowledge instance describes a method to address that symptom.
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23. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises a human characteristics taxonomy, in which each node of the human characteristics taxonomy represents one or more personal human attributes (e.g., address, height, weight, etc.), and an association of a knowledge instance with a node of the human characteristics taxonomy indicates that at least some content of the knowledge instance concerns at least one attribute represented by the node.
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24. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises an entitlement taxonomy, in which each node of the entitlement taxonomy represents an access control level of permission for viewing content or accessing resources of knowledge instances, and an association of a knowledge instance with a node of said entitlement taxonomy indicates that the knowledge instance is to have the access control level specified by that node.
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25. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises a standard taxonomy, in which each node of the standard taxonomy represents one or more topics, and an association of a knowledge instance with a node of the standard taxonomy indicates that at least some content of the knowledge container concerns the topic represented by the node.
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26. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises an environment taxonomy, in which each node of the environment taxonomy represents at least one entity comprising a person.
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27. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises an environment taxonomy, in which each node of the environment taxonomy represents at least one entity comprising a place.
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28. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises an environment taxonomy, in which each node of the environment taxonomy represents at least one entity comprising an organization.
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29. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises an environment taxonomy, in which each node of the environment taxonomy represents at least one entity comprising a product.
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30. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises an environment taxonomy, in which each node of the environment taxonomy represents at least one entity comprising a family of products.
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31. The knowledge map representation of claim 1, wherein at least one of said taxonomies comprises an environment taxonomy, in which each node of the environment taxonomy represents at least one entity comprising a customer segment.
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32. A knowledge map comprising:
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a plurality of separate taxonomies, each separate taxonomy representing a discrete perspective of a knowledge domain; and
wherein each taxonomy comprises nodes and edges connecting nodes, each node corresponding to a conceptual area within the discrete perspective that the taxonomy represents, and each edge representing a relationship between the conceptual areas to which the nodes connected to that edge correspond.
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33. The knowledge map of claim 32, in which each separate taxonomy represents a discrete perspective that is orthogonal to the other discrete perspectives represented by the other separate taxonomies.
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34. The knowledge map of claim 32, further comprising at least one association between a knowledge container and a node, and wherein the association classifies the knowledge container within the knowledge domain.
Specification