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  • 标题:Query Snowball: A Co-occurrence-based Approach to Multi-document Summarization for Question Answering
  • 本地全文:下载
  • 作者:Hajime Morita ; Tetsuya Sakai ; Manabu Okumura
  • 期刊名称:Information and Media Technologies
  • 电子版ISSN:1881-0896
  • 出版年度:2012
  • 卷号:7
  • 期号:3
  • 页码:1124-1129
  • DOI:10.11185/imt.7.1124
  • 出版社:Information and Media Technologies Editorial Board
  • 摘要:We propose a new method for query-oriented extractive multi-document summarization. To enrich the information need representation of a given query, we build a co-occurrence graph to obtain words that augment the original query terms. We then formulate the summarization problem as a Maximum Coverage Problem with Knapsack Constraints based on word pairs rather than single words. Our experiments with the NTCIR ACLIA question answering test collections show that our method achieves a pyramid F3-score of up to 0.313, a 36% improvement over a baseline using Maximal Marginal Relevance.
  • 关键词:question answering;query-oriented;multi-document summarization;information need representation
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