Systems and methods for semantic concept definition and semantic concept relationship synthesis utilizing existing domain definitions

• US 8,495,001 B2
• Filed: 08/28/2009
• Issued: 07/23/2013
• Est. Priority Date: 08/29/2008
• Status: Active Grant

• Current Assignee: Primal Fusion Inc.
• Original Assignee: Primal Fusion Inc.
• Inventors: Sweeney, Peter, Black, Alexander David
• Primary Examiner(s): Chen, Alan
• Assistant Examiner(s): OLUDE AFOLABI, OLATOYOSI
• Application Number:
  US12/549,812
• Publication Number:
  US 20100057664A1
• Time in Patent Office: 1,425 Days
• Field of Search: 706/55, 707/100
• US Class Current: 706/55
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

Computer-implemented systems and methods for synthesis of concept definitions and concept relationships from a domain of data, utilizing different semantic processing protocols such as formal concept analysis and faceted classification synthesis from existing domain concepts that have a confidence gradient built into them. A cognitive or an input agent provides an input of an active concept which is matched against existing domain concepts. The resultant pool of relevant domain concepts is then used to derive virtual concept definitions using a semantic processing protocol. The derivation is then overlaid with a concept of relative proximity of an attribute from another within an attribute set. An additional layer of coherence is given by the relative proximity measure. The end result is a pool of related virtual concept definitions in a tree structure.

Claims

1. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships comprising:

obtaining an active concept definition;

extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions; and

deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves;

wherein the existing real concept definitions are used as a measure of a coherence of various attribute sets.

2. The method of claim 1, deriving additional possible virtual concept definitions using the derived virtual concept definitions.

3. The method of claim 1, wherein the relationships are hierarchical structures.

4. The method of claim 1, wherein a depth of a hierarchy of one derived virtual concept definitions is selectable.

5. The method of claim 4, wherein the selection of the depth of the hierarchy is based upon a confidence gradient.

6. The method of claim 1, wherein a derivable number of virtual concept definitions is limited by quantity.

7. The method of claim 1, wherein derived virtual concept definitions are part of a tree structure.

8. The method of claim 1, wherein the derived virtual concept definitions are in a poly-hierarchal relationship with the real concept definitions.

9. The method of claim 1, wherein the derived virtual concept definitions comprise bins.

10. The method of claim 1, wherein the semantic processing is based upon faceted classification synthesis.

11. The method of claim 1, wherein the semantic processing is based upon formal concept analysis.

12. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships comprising:

obtaining an active concept definition;

extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions; and

deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves;

wherein the derivable number of virtual concept definitions is based upon a qualitative aspect.

13. The method of claim 12, wherein the qualitative aspect is determined by a confidence gradient.

14. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships comprising:

obtaining an active concept definition;

extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions;

deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves; and

searching a plurality of domains to build a selectable quantity of virtual concept definitions.

15. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships comprising:

obtaining an active concept definition;

extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions;

deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves; and

searching a plurality of domains to build selectable depths of hierarchies of virtual concept definitions.

16. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships comprising:

obtaining an active concept definition;

extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions; and

deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves;

wherein the derived virtual concept definitions are in a poly-hierarchal relationship within themselves.

17. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships comprising:

obtaining an active concept definition;

extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions; and

deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves;

wherein a scope of the derived virtual concept definitions is variable with respect to a change in a relative proximity measure between attributes in an attribute set.

18. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships comprising:

obtaining an active concept definition;

extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions; and

deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves;

wherein the semantic processing is based upon faceted classification synthesis;

wherein an attribute substitution rule of replacing parent attributes with child attributes is made optional to synthesize virtual concept definitions.

19. A computer-implemented method to synthesize concept definitions and relationships comprising:

obtaining an active concept definition;

extracting a plural number of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions; and

deriving a plural number of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves;

wherein the method comprises a further step of a final overlay of a concept of relative proximity that further affects selection of attributes.

20. A non-transitory machine-readable medium containing executable computer program instructions which when executed by a data processing system causes the said system to perform a method, the method comprising:

obtaining an active concept definition;

extracting a plural number of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions; and

deriving a plural number of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form a hierarchical structure;

wherein the existing real concept definitions are used as a measure of a coherence of various attribute sets.

21. The non-transitory machine-readable medium of claim 20, wherein the relationships are hierarchical structures.

22. A non-transitory machine-readable medium containing executable computer program instructions which when executed by a data processing system causes the said system to perform a method, the method comprising:

obtaining an active concept definition;

extracting a plural number of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions; and

deriving a plural number of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form a hierarchical structure;

wherein the method comprises a further step of a final overlay of a concept of relative proximity that further affects selection of attributes.

23. A semantic data processing computer system comprising:

at least one tangible memory that stores processor-executable instructions for synthesizing concept definitions and relationships; and

at least one hardware processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to;

obtain an active concept definition;

extract a plural number of real concept definitions comprising attributes from a domain and analyze them for coherence within their attributes;

match the said active concept definition to the extracted real concept definitions; and

derive a plural number of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form a hierarchical structure;

wherein the existing real concept definitions are used as a measure of a coherence of various attribute sets.

24. A semantic data processing computer system comprising:

at least one tangible memory that stores processor-executable instructions for synthesizing concept definitions and relationships; and

at least one hardware processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to;

obtain an active concept definition;

extract a plural number of real concept definitions comprising attributes from a domain and analyze them for coherence within their attributes;

match the said active concept definition to the extracted real concept definitions; and

derive a plural number of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form a hierarchical structure;

wherein the at least one hardware processor executes the processor-executable instructions to overlay a concept of relative proximity that further affects selection of attributes.

25. A non-transitory machine-readable medium containing executable computer program instructions which when executed by a data processing system causes the said system to perform a method, the method comprising:

obtaining an active concept definition;

extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions;

deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves; and

searching a plurality of domains to build a selectable quantity of virtual concept definitions.

26. A semantic data processing computer system comprising:

at least one tangible memory that stores processor-executable instructions for synthesizing concept definitions and relationships; and

at least one hardware processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to;

obtain an active concept definition;

extract a plurality of real concept definitions comprising attributes from a domain and analyze them for coherence within their attributes;

match the said active concept definition to the extracted real concept definitions;

derive a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves; and

search a plurality of domains to build a selectable quantity of virtual concept definitions.

27. A non-transitory machine-readable medium containing executable computer program instructions which when executed by a data processing system causes the said system to perform a method, the method comprising:

obtaining an active concept definition;

extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes;

matching the said active concept definition to the extracted real concept definitions; and

deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves;

wherein the semantic processing is based upon faceted classification synthesis;

wherein an attribute substitution rule of replacing parent attributes with child attributes is made optional to synthesize virtual concept definitions.

28. A semantic data processing computer system comprising:

at least one tangible memory that stores processor-executable instructions for synthesizing concept definitions and relationships; and

at least one hardware processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to;

obtain an active concept definition;

extract a plurality of real concept definitions comprising attributes from a domain and analyze them for coherence within their attributes;

match the said active concept definition to the extracted real concept definitions; and

derive a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves;

wherein the semantic processing is based upon faceted classification synthesis;

wherein an attribute substitution rule of replacing parent attributes with child attributes is made optional to synthesize virtual concept definitions.