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High performance question/answering
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Natural Language Engineering
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
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ICADL'06 Proceedings of the 9th international conference on Asian Digital Libraries: achievements, Challenges and Opportunities
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This paper describes a concept-based approach for question answering system in which concept rather than keyword makes an important role on question analysis, document retrieval, and answer extraction. Our idea is that we can extract correct answer from various paragraphs with different structures when we use well-defined concepts because concepts occurred in questions of same answer type are similar. We defined a concept rule for each answer type. The concept rule contains core concepts occurred in questions of that answer type. Question analysis module extracts concepts from user's question and determines the answer type. Document retrieval module retrieves more relevant documents using extracted concepts. Answer extraction module extracts a probable answer from retrieved documents using concepts. Empirical results show that our concept-based approach can retrieve more relevant documents and extract more accurate answer than any other conventional approach. Also, our approach has additional merits that it is language universal model, and can be combined with arbitrary conventional approaches.