计算机科学 ›› 2009, Vol. 36 ›› Issue (7): 193-196.doi: 10.11896/j.issn.1002-137X.2009.07.046

• 人工智能 • 上一篇    下一篇

基于多策略的单文档问答式信息检索技术

杜永萍 何明   

  1. (北京工业大学计算机学院 北京100124)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金青年基金(No. 60803086),北京工业大学博士科研启动基金(52007012200701)资助。

Multi-strategy Based Single Document Question Answering

DU Yong-ping, HE Ming   

  • Online:2018-11-16 Published:2018-11-16

摘要: 单文档问答式信息检索,即是阅读理解(Reading Comprehension,简称RC)。该任务的目的在于理解一篇文档并对提出的问题返回答案句。提出了充分利用外部资源采用多策略技术来提高RC系统性能的方法,包括基于Web的答案模式匹配应用、词汇语义关联推理以及上下文辅助等策略。本方法使得RC系统性能在Remedia标准测试集上的性能得到提高。描述了不同策略对提高系统性能的有效性,t-test结果表明,运用答案模式匹配和词汇语义关联推理策略所得到的性能显著提高;同时分析了指代消解策略在系统中的关键作用;最后比较了RC任务和多文档问答式信息检索(Question Answering,简称QA)任务的差异性。

关键词: 模式,阅读理解,问题回答,自然语言处理

Abstract: Single document question answering is also called Reading Comprehension(RC),which attempts to understand a document and returns an answer sentence when posed with a question. We proposed an approach that adopted multi-strategy and utilized external knowledge to improve the performance of RC,including pattern matching with Webbased answer patterns,lexical semantic relation inference and context assistance. This approach gives improved RC performance on the Remedia corpus. The effectiveness of different strategy was analyzed and pairwise t-tests show the performance improvements due to Web-derived answer patterns and lexical semantic relation inference technique are statistically significant. In addition, the performance impact by the co-reference resolution was also discussed. Finally, the comparison between the task of RC and multi document question answering(QA) was analyzed.

Key words: Pattern, Reading comprehension, Question answering, Natural language processing

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