计算机应用 ›› 2011, Vol. 31 ›› Issue (11): 3075-3077.DOI: 10.3724/SP.J.1087.2011.03075

• 数据库技术 • 上一篇    下一篇

改进的基于知网的词语相似度算法

王小林1,王义1,2   

  1. 1. 安徽工业大学 计算机学院,安徽 马鞍山 243002
    2. 山东省淄博市周村区人民医院 信息科,山东 淄博 255300
  • 收稿日期:2011-05-10 修回日期:2011-06-26 发布日期:2011-11-16 出版日期:2011-11-01
  • 通讯作者: 王小林
  • 作者简介:王小林(1964-), 男,安徽安庆人,教授,硕士,主要研究方向:人工智能、中文信息处理;
    王义(1974-),男,山东淄博人,工程师,硕士研究生,主要研究方向:中文信息处理。
  • 基金资助:
    国家自然科学基金资助项目;安徽省高校省级自然科学基金资助项目

Improved word similarity algorithm based on HowNet

WANG Xiao-lin1,WANG Yi1,2   

  1. 1. School of Computer, Anhui University of Technology, Maanshan Anhui 243002, China
    2. Information Department, Zhoucun People’s Hospital of Zibo City of Shandong Province, Zibo Shandong 255300, China
  • Received:2011-05-10 Revised:2011-06-26 Online:2011-11-16 Published:2011-11-01
  • Contact: WANG Xiao-lin

摘要: 词语相似度计算在文本分类、问答系统、机器翻译、文本聚类等有着广泛的应用。词语相似度计算的研究工作一般都是基于《知网》的义原的层面上,根据义原之间的距离和义原本身的层次深度,进行词语相似度的计算。基于以上研究,提出了一种新的改进的词语相似度算法,首先根据义项中各类义原的个数不同,提出了一种新的变系数义项相似度计算方法;其次从词性的角度,认为词语义项中的不同词性对词语相似度的贡献度不同,剔除不同词性义项之间的组合。实验结果证明,改进的算法结果在原有基础上得到较好的提升,大幅度降低了相似度计算的复杂度,提高了运算效率。

关键词: 词语相似度, 知网, 义原, 义项, 词性

Abstract: The word similarity computation is widely used in text classification, question-answer system, machine-translation and text clustering. Research of this computation is generally based on HowNet, according to the distance and the depth of sememes. Based on above, an improved method of word similarity computation was proposed as follows. Firstly, a new variable coefficient of homonym similarity computing was proposed according to the count of homonym. Secondly, it took part of speech into account and argued that the part of speech of homonym is different in contributions to word similarity and removed the combinations of homonyms with different part of speech. The experimental results show that the result obtained through this newly-improved computation method is better with less complex calculation and higher calculation efficiency.

Key words: word similarity, HowNet, sememe, homonym, part of speech

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