Intelligent recognition of semantic relationships based on antonymy

Author:

Guan Hui1,Jia Chengzhen1,Yang Hongji2

Affiliation:

1. Department of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, Liaoning, China

2. Department of Informatics University of Leicester, Leicester, England, LE1 7RH, UK

Abstract

Since computing semantic similarity tends to simulate the thinking process of humans, semantic dissimilarity must play a part in this process. In this paper, we present a new approach for semantic similarity measuring by taking consideration of dissimilarity into the process of computation. Specifically, the proposed measures explore the potential antonymy in the hierarchical structure of WordNet to represent the dissimilarity between concepts and then combine the dissimilarity with the results of existing methods to achieve semantic similarity results. The relation between parameters and the correlation value is discussed in detail. The proposed model is then applied to different text granularity levels to validate the correctness on similarity measurement. Experimental results show that the proposed approach not only achieves high correlation value against human ratings but also has effective improvement to existing path-distance based methods on the word similarity level, in the meanwhile effectively correct existing sentence similarity method in some cases in Microsoft Research Paraphrase Corpus and SemEval-2014 date set.

Publisher

IOS Press

Subject

General Computer Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. CONVERGING EXTREMES: OPPOSITE MEANINGS IN ENGLISH TO UKRAINIAN TRANSLATION;Scientific Journal of National Pedagogical Dragomanov University. Series 9. Current Trends in Language Development;2023-06-30

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