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山东大学学报(理学版) ›› 2014, Vol. 49 ›› Issue (11): 59-67.doi: 10.6040/j.issn.1671-9352.3.2014.077

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基于语义场景的隐式篇章关系检测方法

严为绒, 洪宇, 朱珊珊, 车婷婷, 姚建民, 朱巧明   

  1. 苏州大学计算机科学与技术学院, 江苏 苏州 215006
  • 收稿日期:2014-08-28 修回日期:2014-10-21 出版日期:2014-11-20 发布日期:2014-11-25
  • 通讯作者: 洪宇(1978- ),男,博士,副教授,研究方向为篇章分析、话题检测和个性化信息检索. E-mail:tianxianer@gmail.com E-mail:tianxianer@gmail.com
  • 作者简介:严为绒(1988- ),女,硕士研究生,研究方向为篇章分析. E-mail:sallyrong8521@gmail.com
  • 基金资助:
    国家自然科学基金资助项目(61373097, 61272259, 61272260, 90920004);教育部博士学科点专项基金资助项目(2009321110006, 20103201110021);江苏省自然科学基金资助项目(BK2011282);江苏省高校自然科学基金重大项目(11KJA520003);苏州市自然科学基金资助项目(SH201212)

Method of implicit discourse relation detection based on semantics scenario

YAN Wei-rong, HONG Yu, ZHU Shan-shan, CHE Ting-ting, YAO Jian-min, ZHU Qiao-ming   

  1. School of Computer Science and Technology, Soochow University, Suzhou 215006, Jiangsu, China
  • Received:2014-08-28 Revised:2014-10-21 Online:2014-11-20 Published:2014-11-25

摘要: 针对篇章隐式关系检测较难的问题,提出了一种基于语义场景匹配的平行推理方法.该方法利用框架语义学,将论元抽象为概念一级的语义描述(简称语义场景),实现描述形式的压缩.基于大规模静态数据,通过语义场景的匹配挖掘可比较论元辅助关系推理.该方法能够在保证检测精度的同时,提升检测效率.利用宾州篇章树库(penn discourse tree bank, PDTB)对这一检测方法进行评测,检测精度为55.26%.

关键词: 篇章关系, 语义场景, PDTB, 隐式篇章关系

Abstract: The implicit discourse relation detection has a higher difficulty. For this, a method was proposed to detect implicit discourse relation based on semantics scenario. The compression of description form was realized by frame semantics that abstract argument as conceptual semantic description (semantics scenario), and then mine the comparable argument pairs through semantics scenario from large-scale static data. It can ensure accuracy while improve detection efficiency. The discourse relation was detected in Penn Discourse Treebank (PDTB). The accuracy can reach to 55.26%.

Key words: implicit discourse relation, discourse relation, semantics scenario, PDTB

中图分类号: 

  • TP391
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