Name
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s13042-020-01069-8 | International Journal of Machine Learning and Cybernetics |
Keywords | DocType | Volume |
Word representation, Static embedding, Dynamic embedding, Cross-lingual embedding | Journal | 11 |
Issue | ISSN | Citations |
7 | 1868-8071 | 2 |
PageRank | References | Authors |
0.37 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxuan Wang | 1 | 2 | 0.37 |
| Yutai Hou | 2 | 3 | 3.43 |
| Wanxiang Che | 3 | 711 | 66.39 |
| Ting Liu | 4 | 2735 | 232.31 |