2006 Fiscal Year Final Research Report Summary
An Inference Method to Obtain Approximate Solutions under Incomplete Knowledge
| Project/Area Number |
15560351
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
System engineering
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| Research Institution | Takushoku University |
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Principal Investigator |
ISHIKAWA Tsutomu Takushoku University, Faculty of Engineering, Professor, 工学部, 教授 (10281370)
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| Project Period (FY) |
2003 – 2006
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| Keywords | inference scheme / common knowledge base / knowledge representation / order-sorted logic / knowledge base of words / measurement of similarity |
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| Research Abstract |
We have studied an inference scheme to obtain approximate solutions under incomplete knowledge and the common knowledge bases used in the inference, aiming at realization of the same flexible processing as human.
Concerning the former, we have improved the inference method developed before, called ARSK (Approximate Reasoning with Similar Knowledge), which derives approximate solutions using similar knowledge, and have proposed a new knowledge representation scheme for it, called WPL (Word-based Predicate Logic). WPL is a kind of extended order-sorted logic. Both a simple sentence and a complex sentence are transformed to one atomic formula with structured sort symbols using the existent natural language processing tools. The inference processes are executed by semantically interpreting sort symbols, which consist of multiple ordinary words, word by word. We have proposed the new inference rules which can deal with such a complex sort symbols.
We have also developed and evaluated a tool measuring the semantic similarity between words by using both the knowledge base of words, which was constructed based on Japanese dictionaries and an existent thesaurus. The evaluation result shows that this tool can obtain nearly the same performance in the accuracy as human judgment.
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