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Question Answering System Using Web Relevance Score and Translation Probability
Yuji Abe, Hajime Morita, Kanako Komiya, Yoshiyuki Kotani
11 - 15
10.3233/978-1-61499-094-9-11
Frontiers in Artificial Intelligence and Applications
Volume 240: Knowledge-Based Software Engineering
Abstract

Question Answering (QA) is a task of answering natural language question with an adequate sentence. This paper proposes the method to evaluate candidate answer sentences using two methods, i.e., the Web relevance score and the translation probability. The experiments revealed the proposed method was significantly better than the original methods when MRRs were compared.

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