Thunlp Topical Word Embeddings Save
Topical Word Embeddings
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topical_word_embeddings
This is the implement for a paper accepted by AAAI2015.
hope to be helpful for your research in NLP and IR.
If you use the code, please cite this paper:
Yang Liu, Zhiyuan Liu, Tat-Seng Chua, Maosong Sun. Topical Word Embeddings. The 29th AAAI Conference on Artificial Intelligence (AAAI'15).
There are some mistakes in our Text Classification F-measue, the accurate result are list here:
| Model | Accuracy | Precison | Recal | F-measure |
|---|---|---|---|---|
| BOW | 79.7 | 79.5 | 79.0 | 79.2 |
| LDA | 72.2 | 70.8 | 70.7 | 70.7 |
| Skip-Gram | 75.4 | 75.1 | 74.7 | 74.9 |
| PV-DM | 72.4 | 72.1 | 71.5 | 71.8 |
| PV-DBOW | 75.4 | 74.9 | 74.3 | 74.6 |
| TWE-1 | 81.5 | 81.2 | 80.6 | 80.9 |
| TWE-2 | 79.0 | 78.6 | 77.9 | 78.2 |
| TWE-3 | 77.4 | 77.2 | 76.2 | 76.7 |
Open Source Agenda is not affiliated with "Thunlp Topical Word Embeddings" Project. README Source: thunlp/topical_word_embeddings
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