Fulian Yin, Yanyan Wang, Jianbo Liu*, Meiqi Ji
CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 747-764, 2020, DOI:10.32604/cmes.2020.010579
- 20 July 2020
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 More >
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