Populating an expert-system knowledgebase based on correspondences between knowledgebase axioms and business processes

Patent metadata

Field	Value
Publication number	US-11501087-B2
Application number	US-201916556820-A
Country	US
Kind code	B2
Filing date	Aug 30, 2019
Priority date	Jun 27, 2013
Publication date	Nov 15, 2022
Grant date	Nov 15, 2022

Abstract

A knowledgebase of an expert system is populated with rules inferred from a set of business processes that govern the manner in which the business interacts with users. Each business process contains an input, an output, an action, and a set of dependency relationships that relate pairs of the input, the output, and the action. Each process's input, output, action, and dependency relationships are translated, respectively, into a subject, an object, a predicate, and a set of dependency relationships among the subject, object, and predicate, of a natural-language rule. Each rule is stored in the expert system's knowledgebase as a directed graph, and nodes representing each stored subject, object, and predicate are assigned domain classifications as a function of characteristics of the business rule. These domain classifications are represented within the knowledgebase as a set of domain classifications determined as a further function of characteristics of the business rule.

First claim

What is claimed is:

1. A method for populating an expert system knowledgebase with an axiom that represents a business process, the method comprising:
a processor of a computer system identifying a correspondence between a business process and an axiom,
where the axiom comprises a rule identifying how the expert system should respond during natural-language interactions with a user,
where the axiom comprises a subject, an object, a predicate, and rule relationships among the subject, the object, and the predicate,
where the business process comprises an input, an output, an action, and process dependencies among the input, the output, and the action,
where the correspondence identifies the subject as corresponding to the input, the object as corresponding to the output, and the predicate as corresponding to the action, and
where the correspondence further identifies a correspondence between each rule relationship and a corresponding process relationship; and

the processor representing the business process by adding to a directed graph that represents axioms stored in the knowledgebase:
three nodes that respectively represent the subject, the object, and the predicate, and
a set of edges that each connect one pair of the subject, the object, and the predicate, and that each represent one of the process dependencies between the connected pair.

2. The method of claim 1 , where the axiom is a rule for formulating a natural-language reply to a user question submitted during the natural-language interactions.

3. The method of claim 1 , where the axiom is a rule for inferring semantic meaning from the natural-language interactions as a function of the business process.

4. The method of claim 1 , where the axiom is a rule for inferring additional rules from the natural-language interactions.

5. The method of claim 1 , where the axiom is a rule for selecting, in response to receiving user input during the natural-language interactions, a second axiom stored in the knowledgebase.

6. The method of claim 1 , where the knowledgebase is automatically populated as a function of information comprised by the set of business processes.

7. The method of claim 1 ,
where a classification of a set of classifications is represented as a first classification node of the directed graph,
where the set of classifications comprises a set of concept classifications and a set of activity classifications,
where a first concept classification of the set of concept classifications associates an input domain with the input and with the subject,
where a second concept classification of the set of concept classifications associates an output domain with the output and with the object,
where a first activity classification of the set of activity classifications associates an action domain with the action and with the predicate,
where a first classification relationship identifies a dependency relationship between a pair of classifications of the set of classifications, and where the first classification relationship is a function of a characteristic of the first business process, and
where the representing the business process further comprises adding to the directed graph, as a further function of the characteristic, an edge representing the first classification relationship as a first classification dependency of the process dependencies.

8. The method of claim 1 , further comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable program code in the computer system, where the computer-readable program code in combination with the computer system is configured to implement the identifying and the representing.

9. A computer program product, comprising a computer-readable hardware storage device having a computer-readable program code stored therein, said program code configured to be executed by a processor of a computer system to implement a method for populating an expert system knowledgebase with an axiom that represents a business process, the method comprising:
the processor identifying a correspondence between a business process and an axiom,
where the axiom comprises a rule identifying how the expert system should respond during natural-language interactions with a user,
where the axiom comprises a subject, an object, a predicate, and rule relationships among the subject, the object, and the predicate,
where the business process comprises an input, an output, an action, and process dependencies among the input, the output, and the action,
where the correspondence identifies the subject as corresponding to the input, the object as corresponding to the output, and the predicate as corresponding to the action, and
where the correspondence further identifies a correspondence between each rule relationship and a corresponding process relationship; and

the processor representing the business process by adding to a directed graph that represents axioms stored in the knowledgebase:
three nodes that respectively represent the subject, the object, and the predicate, and
a set of edges that each connect one pair of the subject, the object, and the predicate, and that each represent one of the process dependencies between the connected pair.

10. The computer program product of claim 9 , where the axiom is a rule for formulating a natural-language reply to a user question submitted during the natural-language interactions.

11. The computer program product of claim 9 , where the axiom is a rule for inferring semantic meaning from the natural-language interactions as a function of the business process.

12. The computer program product of claim 9 , where the axiom is a rule for inferring additional rules from the natural-language interactions.

13. The computer program product of claim 9 , where the axiom is a rule for selecting, in response to receiving user input during the natural-language interactions, a second axiom stored in the knowledgebase.

14. The computer program product of claim 9 ,
where a classification of a set of classifications is represented as a first classification node of the directed graph,
where the set of classifications comprises a set of concept classifications and a set of activity classifications,
where a first concept classification of the set of concept classifications associates an input domain with the input and with the subject,
where a second concept classification of the set of concept classifications associates an output domain with the output and with the object,
where a first activity classification of the set of activity classifications associates an action domain with the action and with the predicate,
where a first classification relationship identifies a dependency relationship between a pair of classifications of the set of classifications, and where the first classification relationship is a function of a characteristic of the first business process, and
where the representing the business process further comprises adding to the directed graph, as a further function of the characteristic, an edge representing the first classification relationship as a first classification dependency of the process dependencies.

15. A computer system comprising a processor, a memory coupled to said processor, and a computer-readable hardware storage device coupled to said processor, said storage device containing program code configured to be run by said processor via the memory to implement a method for populating an expert system knowledgebase with an axiom that represents a business process, the method comp

Assignees

• IBM

Inventors

• Byron Donna K
• Katahira Reinaldo T
• Krishnamurthy Lakshminarayanan
• Trim Craig M

Classifications

• G06N5/02 Primary

  Knowledge representation; Symbolic representation · CPC title

• G06N5/046

  Forward inferencing; Production systems · CPC title

• G06F40/55 Primary

  Rule-based translation · CPC title