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Building spatial temporal relation graph of concepts pair using web repository

机译:使用Web存储库构建概念对的空间时间关系图

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摘要

Mining semantic relations between concepts underlies many fundamental tasks including natural language processing, web mining, information retrieval, and web search. In order to describe the semantic relation between concepts, in this paper, the problem of automatically generating spatial temporal relation graph (STRG) of semantic relation between concepts is studied. The spatial temporal relation graph of semantic relation between concepts includes relation words, relation sentences, relation factor, relation graph, faceted feature, temporal feature, and spatial feature. The proposed method can automatically generate the spatial temporal relation graph (STRG) of semantic relation between concepts, which is different from the manually generated annotation repository such as WordNet and Wikipedia. Moreover, the proposed method does not need any prior knowledge such as ontology or the hierarchical knowledge base such as WordNet. Empirical experiments on real dataset show that the proposed algorithm is effective and accurate.
机译:挖掘概念之间的语义关系是许多基本任务的基础,包括自然语言处理,Web挖掘,信息检索和Web搜索。为了描述概念之间的语义关系,本文研究了自动生成概念之间语义关系的时空关系图(STRG)的问题。概念之间语义关系的时空关系图包括关系词,关系语句,关系因子,关系图,分面特征,时间特征和空间特征。所提出的方法可以自动生成概念之间语义关系的时空关系图(STRG),这与手动生成的注释库(如WordNet和Wikipedia)不同。而且,所提出的方法不需要诸如本体之类的任何先验知识或诸如WordNet之类的分层知识库。在真实数据集上的经验实验表明,该算法是有效且准确的。

著录项

  • 来源
    《Information systems frontiers》 |2017年第5期|1029-1038|共10页
  • 作者单位

    Minist Publ Secur, Res Inst 3, Shanghai, Peoples R China|Tsinghua Univ, Beijing, Peoples R China;

    Shanghai Univ, Shanghai, Peoples R China;

    Minist Publ Secur, Res Inst 3, Shanghai, Peoples R China;

    Univ Texas San Antonio, Dept Informat Syst & Cyber Secur, San Antonio, TX USA|Univ South Australia, Sch Informat Technol & Math Sci, Adelaide, SA, Australia|China Univ Geosci, Sch Comp Sci, Wuhan, Hubei, Peoples R China;

    Minist Publ Secur, Res Inst 3, Shanghai, Peoples R China;

    Minist Publ Secur, Res Inst 3, Shanghai, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Knowledge graph; Semantic relations; Web repository; Temporal and spatial mining;

    机译:知识图;语义关系;Web资料库;时空挖掘;

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