| Autor: |
Shui-fei ZENG, Xiao-yan ZHANG, Xiao-feng DU, Tian-bo LU |
| Jazyk: |
čínština |
| Rok vydání: |
2017 |
| Předmět: |
|
| Zdroj: |
Tongxin xuebao, Vol 38, Pp 86-98 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
1000-436X |
| DOI: |
10.11959/j.issn.1000-436x.2017088 |
| Popis: |
Method of text representation model was proposed to extract word-embedding from text feature.Firstly,the word-embedding of the dual word-embedding list based on dictionary index and the corresponding part of speech index was created.Then,feature vectors was obtained further from these extracted word-embeddings by using Bi-LSTM recurrent neural network.Finally,the sentence vectors were processed by mean-pooling layer and text categorization was classified by softmax layer.The training effects and extraction performance of the combination model of Bi-LSTM and double word-embedding neural network were verified.The experimental results show that this model not only performs well in dealing with the high-quality text feature vector and the expression sequence,but also significantly outperforms other three kinds of neural networks,which includes LSTM,LSTM+context window and Bi-LSTM. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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