[1]李蕾,杨丽花.基于知网的词语语义相似度改进算法[J].计算机技术与发展,2019,29(04):42-46.[doi:10. 3969 / j. issn. 1673-629X. 2019. 04. 009]
　LI Lei,YANG Li-hua.Improved Algorithm of Word Semantic Similarity Based on HowNet[J].,2019,29(04):42-46.[doi:10. 3969 / j. issn. 1673-629X. 2019. 04. 009]
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基于知网的词语语义相似度改进算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年04期
页码:
42-46
栏目:
智能、算法、系统工程
出版日期:
2019-04-10

文章信息/Info

Title:
Improved Algorithm of Word Semantic Similarity Based on HowNet
文章编号:
1673-629X(2019)04-0042-05
作者:
李蕾; 杨丽花
南京邮电大学 江苏省无线通信重点实验室,江苏 南京 210003
Author(s):
LI Lei; YANG Li-hua
Key Laboratory of Wireless Communication of Jiangsu Province,Nanjing University of Posts and Telecommunications,Nanjing 210003,China
关键词:
知网; 词语语义相似度; 义原密度; 义原深度; 义原距离
Keywords:
HowNet; semantic similarity of words; density of sememe; depth of sememe; distance of sememe
分类号:
TP311
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 04. 009
摘要:
词语语义相似度计算在很多领域都有广泛应用,而目前常用的基于知网的词语语义相似度计算方法由于未深入考虑同一棵树中的两个不同义原的可达路径上所有义原节点的密度对义原距离的影响,或未考虑义原深度与义原密度的主次关系,导致计算结果不够精确,从而使其应用受限。针对该问题,给出了一个新的节点间边权重函数,通过在边权重函数中引入两义原可达路径上所有义原节点的密度,并利用权重因子来调整义原深度和义原密度对义原距离的影响,从而提出一种改进的基于知网的词语语义相似度计算方法。实验结果表明,该方法可以更有效地提高词语语义相似度计算精度,比现有方法更具有实用性。
Abstract:
Semantic similarity of words has been widely used in many fields. The current word semantic similarity calculation method based on HowNet does not deeply consider the influence of the density of all the semantically original nodes on the reachable path of two different sememes in the same tree,or also does not consider in depth with the primary and secondary relationship between the density and the depth of sememe,which causes the calculation result to be inaccurate. To solve the problem,we propose a new method using the density of all sememe nodes on the reachable path in the edge weight function,and the proposed method employs the weight factor to adjust the influence of the depth of sememe and the density of sememe on the distance of sememe. The simulation shows that the proposed algorithm can effectively improve the accuracy of the semantic similarity calculation of words,and is more practical than the existing methods.

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更新日期/Last Update: 2019-04-10