| Project/Area Number |
15500144
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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 |
Sensitivity informatics/Soft computing
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| Research Institution | Meiji University |
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Principal Investigator |
MUKAIDONO Masao (2004-2005) Meiji University, Computer Science, Professor, 理工学部, 教授 (00061987)
高木 友博 (2003) 明治大学, 理工学部, 教授 (90308065)
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| Co-Investigator(Kenkyū-buntansha) |
AIZAWA Shouko National Institute of Informatics, Professor, 情報基盤研究系情報流通基盤研究部門, 教授 (90222447)
向殿 政男 明治大学, 理工学部, 教授 (00061987)
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| Project Period (FY) |
2003 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2005: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2004: ¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 2003: ¥1,300,000 (Direct Cost: ¥1,300,000)
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| Keywords | conceptual fuzzy sets / fuzzy sets / information retrieval / fuzzy similarity measure / context dependency / ソフトコンピューティング / サーチエンジン / ファジィ |
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| Research Abstract |
Ambiguity in language is one of the most difficult problems in dealing with word senses using computers. Word senses vary dynamically depending on context. We must specify the context to identify them. We propose here a method to represent such senses using conceptual fuzzy sets. First, we used the modified confabulation model (a prediction method similar to the n-gram model) and word sequences just before the target word to generate atomic conceptual fuzzy sets automatically. Then we generated conceptual fuzzy sets depending on context using the atomic fuzzy sets and a relationship based on cooccurrences. We used a large corpus consisting of 1 million newswire text data in our experiments. The results of these tasks demonstrated that our methodology was effective to generate conceptual fuzzy sets depending on context.
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