EP0334113A2
Expired / Lapsed
EP
⏱️ 0.0 years remaining
Expert system inference engine
Assignee: International Business Machines Corp
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Filing: 1989-03-09
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Granted: —
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Expires: 2009-03-09
Abstract
Abstract An expert system (31) includes a knowledge base manager which is fact-based, as opposed to rule-based; i.e., a semantic network with tangled hierarchies. The system includes an inference engine which is capable of providing solutions to indeterminate problems with a high degree of confidence. "Entities" (e.g., propositions, facts and ideas) are understood in eight different ways depending on the context of entity relationships. Each such relationship may be characterized anywhere along a spectrum from strong to weak. The knowledge base is designed so that entities and relationships are easily modified. The Result is based on the above-mentioned user-inputs and an inference engine able to handle dubious certainty.
Inventors
- 👤 Irwin Tyler
Bibliographic Details
Application Number
—
Jurisdiction
EP
Data Source
google_patents
Last Synchronized
2026-11-01 15:28
CPC Classifications
G; G06; G06N; G06N5/00; G06N5/02; G06N5/04
Claims Analysis
Total Claims: 5
Claim 1
Independent Claim
85 words
A method of inference processing in a fact-based expert system comprising the steps of: generating a knowledge base by inputting and linking conceptual entities to create a network; assigning a qualitative value to relationships between entities; processing said knowledge base to solve a problem within a domain defined by said network by traversing said network following all linkages forward and backward; adjusting and accumulating said qualitive values for each entity processed; and generating a result and confidence measure thereof based on the assigned relationship values.
Claim 2
Independent Claim
85 words
A method of inference processing in a fact-based expert system comprising the steps of: generating a knowledge base by inputting and linking conceptual entities to create a network; assigning a qualitative value to relationships between entities; processing said knowledge base to solve a problem within a domain defined by said network by traversing said network following all linkages forward and backward; adjusting and accumulating said qualitive values for each entity processed; and generating a result and confidence measure thereof based on the assigned relationship values.
Claim 3
Independent Claim
107 words
A method of inference processing in a fact-based expert system comprising the steps of: generating a knowledge base by inputting assertions, assigning confidence levels to the assertions, and linking the assertions to create a network; processing said knowledge base to solve a problem within a domain made up of a network of linked assertions by traversing said network following all linkages forward and backward, and for each completed supporting assertion, retrieving its stated or inferred influence and confidence while following user directives to ignore specified supporting assertions and then normalizing an inference for completed assertions; and posting the results of said processing step with a confidence level.
Claim 4
Independent Claim
107 words
A method of inference processing in a fact-based expert system comprising the steps of: generating a knowledge base by inputting assertions, assigning confidence levels to the assertions, and linking the assertions to create a network; processing said knowledge base to solve a problem within a domain made up of a network of linked assertions by traversing said network following all linkages forward and backward, and for each completed supporting assertion, retrieving its stated or inferred influence and confidence while following user directives to ignore specified supporting assertions and then normalizing an inference for completed assertions; and posting the results of said processing step with a confidence level.
Claim 5
Dependent Claim
55 words
The method according to claim 2 further comprising, for each completed supporting assertion, the steps of: adjusting stated or inferred influence according to a strength and confidence adjustment algorithm; applying an arithmetic sign according to a context direction of the assertion; and accumulating a confidence level for the assertion according to a confidence adjustment algorithm.
References Cited (Backward Citations)
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