Systems and methods for semantic concept definition and semantic concept relationship synthesis utilizing existing domain definitions
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.
1. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships, the method comprising:
using the computer to perform:
obtaining an active concept definition;
extracting a plurality of real concept definitions;
analyzing the plurality of real concept definitions for their attribute set coherence within a context of the active concept definition;
matching the 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 at least one domain to build selectable depths of hierarchies of virtual concept definitions,
wherein a derivable number of virtual concept definitions is determined based on a confidence gradient.
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 definition is selectable.
5. The method of claim 4 , wherein the selection of the depth of the hierarchy is based upon the confidence gradient.
6. The method of claim 1 , wherein the derivable number of virtual concept definitions is limited by quantity.
7. The method of claim 1 , wherein the derivable number of virtual concept definitions is based upon a qualitative aspect.
8. The method of claim 7 , wherein the qualitative aspect is determined by the confidence gradient.
9. The method of claim 1 , further comprising searching a plurality of domains to build a selectable quantity of virtual concept definitions.
10. The method of claim 1 , wherein the derived virtual concept definitions are in a polyhierarchical relationship within themselves.
11. The method of claim 1 , wherein the existing real concept definitions are used as a measure of a coherence of various attribute sets.
12. The method of claim 1 , wherein derived virtual concept definitions are part of a tree structure.
13. The method of claim 1 , wherein the derived virtual concept definitions are in a polyhierarchical relationship with the real concept definitions.
14. The method of claim 1 , 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.
15. The method of claim 1 , wherein the derived virtual concept definitions comprise bins.
16. The method of claim 1 , wherein the semantic processing is based upon faceted classification synthesis.
17. The method of claim 16 , wherein an attribute substitution rule of replacing parent attributes with child attributes is made optional to synthesize virtual concept definitions.
18. The method of claim 1 , wherein the semantic processing is based upon formal concept analysis.