JOURNAL ARTICLE

Chinese long text summarization using improved sequence-to-sequence lstm

Zanjie YaoAixiang ChenHan Xie

Year: 2020 Journal:   Journal of Physics Conference Series Vol: 1550 (3)Pages: 032162-032162   Publisher: IOP Publishing

Abstract

Abstract Text summarization is an important issue in natural language processing. The existing method has the problem of low accuracy when performing long text summarization. In this paper, We use the LSTM to construct the sequence-to-sequence model, and combine the attention mechanism to process automatic Chinese long text summarization.The experimental results indicate that our method can accurately extract key information from long text, generate high-quality summary.

Keywords:
Automatic summarization Computer science Sequence (biology) Natural language processing Text graph Construct (python library) Artificial intelligence Multi-document summarization Process (computing) Key (lock) Information retrieval Programming language

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1
Cited By
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FWCI (Field Weighted Citation Impact)
21
Refs
0.07
Citation Normalized Percentile
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Citation History

Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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