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基于事件的文本表示方法研究 被引量:7

Research on Event-based Method for Text Representation
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摘要 在传统文本表示模型的研究基础上,针对叙事类文本,考虑以事件作为基本语义单元,并结合图结构表示的特点,提出了一种基于事件的文本表示方法——事件网络。该方法利用事件和事件间的关系来表示文本,能够较大程度地保留文本的结构信息及语义信息。实验结果表明,基于该方法的自动摘要取得了较好的效果。 By studying some traditional text representation models,this paper considered the event as a basic semantic unit for narrative texts,and presented a new event-based text representation method(Event-Network),which combines the characteristics of the graph structure.This method uses events and the relationship between events to represent the text,and can retain the structure information and semantic information of the text to a greater extent.The experimental results show that automatic summary based on the method has better performance.
出处 《计算机科学》 CSCD 北大核心 2012年第12期188-191,共4页 Computer Science
基金 国家自然科学基金项目(60975033) 安徽省高等学校优秀青年人才基金项目(2010SQRL050)资助
关键词 文本表示 图结构 事件相似度 事件网络 Text representation Graph structure Event similarity Event-network
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  • 1Chen X. Why did John Herschel fail to understand polarization? The differences between object and event concepts[J]. Studies inHistory and Philosophy of Science, 2003,34 : 491-513.
  • 2Baeza-Yates R, Ribeiro-Neto B. Modern Information Retrieval [M]. Addison-Wesley- Longman, Reading, MA, 1999.
  • 3Salton G, Buckley C. Term-weighting approaches in automatic text retrieval [J]. Information Processing and Management, 1988,24(5) : 513-523.
  • 4Wei Xing,Croft W. LDA-based document models for ad-hoc re- trieval[C]//Proceedings of the 29th SIGIR Conference. Seattle, Washington, USA, 2006 : 178-185.
  • 5Robertson S E, Walker S, Jones S, et al. Okapi TREC-4[C] // Proceeding of The 4th Text Retrieval Conference. 1996:500-236.
  • 6Schenker A, Last M, Bunke H, et al. Graph Representations for Web Documents Clustering[C]//LNCS on Pattern Recognition and Image Analysis. Springer Berlin, 2003 : 935-942.
  • 7Hensman S. Construction of conceptual graph representation of texts[C]//Proceeding of the Student Research Workshop at HL T-NAACL. 2004,49-54.
  • 8Bhoopesh,Pushpak. Text clustering using Semantics[C]//Pro- ceeding of the 11th International World Wide Web Conference. 2002 : 78-84.
  • 9Mani I, Bloedorn E. Multi-document Summarization by Graph Search and Matching[C]//Proceeding of the 15th National Con- ference on Artificial Inteligence. 1997:622-628.
  • 10Jin W, Srihari R K. Graph-based Text Representation and Knowledge Discovery[C]//Proceedings of the 2007 ACM Sym- posium on Applied Computing. Seoul, Korea, New York, NY, USA: ACM, 2007 : 807-811.

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