Improved Semantic Similarity Method Based on HowNet for Text Clustering

被引：0

作者：

Nie, Hongmei ^{[1
]}

Zhou, Jiaqing ^{[2
]}

Guo, Qi ^{[1
]}

Huang, Zhiqi ^{[1
]}

机构：

[1] Zhejiang Normal Univ, Math Phys & Informat Engn Coll, Jinhua, Peoples R China

[2] Zhejiang Normal Univ, Xingzhi Coll, Jinhua, Peoples R China

来源：

2018 5TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE 2018) | 2018年

关键词：

semantic similarity; HowNet; sememe; weights; matching; clustering;

D O I：

10.1109/ICISCE.2018.00063

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new semantic similarity method based on HowNet is proposed in this paper. At the level of concept, the sememes are divided into several classes. In this paper, the ordering of the weights of the sememe classes is considered. At the same time, a function is reasonably set to make the weights change moderately, which solves the problem of excessive reliance on fixed weights. Moreover, for the similarity between two texts, the element matching method is proposed in this paper. Experimental results show that the proposed method makes the text clustering results more accurate and reasonable compared with the existing methods.

引用

页码：266 / 269

页数：4

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