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From static to dynamic word representations: a survey.

Authors :
Wang, Yuxuan
Hou, Yutai
Che, Wanxiang
Liu, Ting
Source :
International Journal of Machine Learning & Cybernetics; Jul2020, Vol. 11 Issue 7, p1611-1630, 20p
Publication Year :
2020

Abstract

In the history of natural language processing (NLP) development, the representation of words has always been a significant research topic. In this survey, we provide a comprehensive typology of word representation models from a novel perspective that the development from static to dynamic embeddings can effectively address the polysemy problem, which has been a great challenge in this field. Then the survey covers the main evaluation metrics and applications of these word embeddings. And, we further discuss the development of word embeddings from static to dynamic in cross-lingual scenario. Finally, we point out some open issues and future works. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18688071
Volume :
11
Issue :
7
Database :
Complementary Index
Journal :
International Journal of Machine Learning & Cybernetics
Publication Type :
Academic Journal
Accession number :
143738497
Full Text :
https://doi.org/10.1007/s13042-020-01069-8