Summarizing relevant information for question-answering using hybrid relevance analysis and surface feature salience

Jen Yuan Yeh*, Hao-Ren Ke, Wei Pang Yang

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

摘要

Much research for question-answering aims to answer factiod, definitional and biographical questions. In most cases, the answers are given as a name, date, quantity, and so on. In this paper, we try to merge techniques of multidocument summarization and question-answering to generate a brief, well-organized fluent summary to provide more relevant information for the purpose of answering real-world complicated questions. The problem is addressed as a query-biased sentence retrieval task. We propose a hybrid relevance analysis to evaluate the relevance of a sentence to the query. The summary is created by including sentences with the topmost significances which are measured in terms of sentence relevance and surface feature salience. In addition, a modified Maximal Marginal Relevance is proposed for anti-redundancy. The proposed approach was evaluated with the DUC 2005 corpus and found to perform well with competitive results.

原文英語
頁(從 - 到)2549-2556
頁數8
期刊WSEAS Transactions on Information Science and Applications
3
發行號12
出版狀態已發佈 - 2006 十二月 1

ASJC Scopus subject areas

  • 資訊系統
  • 電腦科學應用

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