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Enhancing Embedding-Based Chinese Word Similarity Evaluation with Concepts and Synonyms Knowledge

Fulian Yin, Yanyan Wang, Jianbo Liu*, Meiqi Ji

Communication University of China, Beijing, 100024, China

* Corresponding Author: Jianbo Liu. Email: email

(This article belongs to the Special Issue: Information Hiding and Multimedia Security)

Computer Modeling in Engineering & Sciences 2020, 124(2), 747-764. https://doi.org/10.32604/cmes.2020.010579

Abstract

Word similarity (WS) is a fundamental and critical task in natural language processing. Existing approaches to WS are mainly to calculate the similarity or relatedness of word pairs based on word embedding obtained by massive and high-quality corpus. However, it may suffer from poor performance for insuf- ficient corpus in some specific fields, and cannot capture rich semantic and sentimental information. To address these above problems, we propose an enhancing embedding-based word similarity evaluation with character-word concepts and synonyms knowledge, namely EWS-CS model, which can provide extra semantic information to enhance word similarity evaluation. The core of our approach contains knowledge encoder and word encoder. In knowledge encoder, we incorporate the semantic knowledge extracted from knowledge resources, including character-word concepts, synonyms and sentiment lexicons, to obtain knowledge representation. Word encoder is to learn enhancing embedding-based word representation from pre-trained model and knowledge representation based on similarity task. Finally, compared with baseline models, the experiments on four similarity evaluation datasets validate the effectiveness of our EWS-CS model in WS task.

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APA Style
Yin, F., Wang, Y., Liu, J., Ji, M. (2020). Enhancing embedding-based chinese word similarity evaluation with concepts and synonyms knowledge. Computer Modeling in Engineering & Sciences, 124(2), 747-764. https://doi.org/10.32604/cmes.2020.010579
Vancouver Style
Yin F, Wang Y, Liu J, Ji M. Enhancing embedding-based chinese word similarity evaluation with concepts and synonyms knowledge. Comput Model Eng Sci. 2020;124(2):747-764 https://doi.org/10.32604/cmes.2020.010579
IEEE Style
F. Yin, Y. Wang, J. Liu, and M. Ji "Enhancing Embedding-Based Chinese Word Similarity Evaluation with Concepts and Synonyms Knowledge," Comput. Model. Eng. Sci., vol. 124, no. 2, pp. 747-764. 2020. https://doi.org/10.32604/cmes.2020.010579

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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