A Neural Generative Model for Joint Learning Topics and Topic-Specific Word Embeddings (2020.tacl-1)
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| Challenge: | Experimental results show that the proposed model outperforms word-level embedding methods in word similarity evaluation and word sense disambiguation. |
| Approach: | They propose a generative model that explores local and global context for joint learning topics and topic-specific word embeddings. |
| Outcome: | The proposed model outperforms word-level embedding methods in word similarity evaluation and word sense disambiguation. |
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