Measuring Semantic Similarity between Words Based on Multiple Relational Information

Jianyong DUAN  Yuwei WU  Mingli WU  Hao WANG  

IEICE TRANSACTIONS on Information and Systems   Vol.E103-D   No.1   pp.163-169
Publication Date: 2020/01/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2019EDP7083
Type of Manuscript: PAPER
Category: Natural Language Processing
semantic similarity,  representation learning,  multiple-relation,  

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The similarity of words extracted from the rich text relation network is the main way to calculate the semantic similarity. Complex relational information and text content in Wikipedia website, Community Question Answering and social network, provide abundant corpus for semantic similarity calculation. However, most typical research only focused on single relationship. In this paper, we propose a semantic similarity calculation model which integrates multiple relational information, and map multiple relationship to the same semantic space through learning representing matrix and semantic matrix to improve the accuracy of semantic similarity calculation. In experiments, we confirm that the semantic calculation method which integrates many kinds of relationships can improve the accuracy of semantic calculation, compared with other semantic calculation methods.