关联图谱的研究进展及面临的挑战

摘要/Abstract

摘要： 随着Web技术的不断发展和Linked Open Data等项目的相继开展,关联图谱已被广泛应用于互联网智能搜索、图书馆书目管理、医学、智能制造等领域,并取得了显著的成果。文中深刻阐述了关联图谱的定义、架构以及构建的关键技术,包括实体抽取、实体间关系抽取和知识融合等方面的研究进展,并深度分析了当前关联图谱分析与研究所面临的若干挑战问题。

关键词: 关联图谱, 关系抽取, 实体抽取, 知识融合

Abstract: With the development of web technology and projects such as Linked Open Data having been carried out,the association graph has made significant contributions on many areas such as Internet intelligent search,library bibliographic management,medicine and intelligent manufacturing.This paper reviewed the key topics of the association graph,including definition,framework and construction etc.The research progress on entity extraction,relationship extraction and knowledge fusion are discussed thoroughly.Furthermore,some challenges on association graph are also summarized.

Key words: Association graph, Entity extraction, Knowledge fusion, Relation extraction

中图分类号:

TP391

尹亮, 袁飞, 谢文波, 王栋志, 孙崇敬. 关联图谱的研究进展及面临的挑战[J]. 计算机科学, 2018, 45(6A): 1-10. https://doi.org/

YIN Liang, YUAN Fei, XIE Wen-bo, WANG Dong-zhi, SUN Chong-jing. Research Progress and Challenges on Association Graph[J]. Computer Science, 2018, 45(6A): 1-10. https://doi.org/

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