A Machine Learning Approach to Extract Keyphrases from Bengali Document using CNN-Bidirectional LSTM

computer and information technology(2019)

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摘要
Keyphrases are single or multiple word phrases of a document which describe the principal topics of that document. These keyphrases help readers to get an overview of the document. In this paper, we proposed a system that uses the combination of Convolutional Neural Network and Bidirectional Long Short-Term Memory (BiLSTM) Recurrent Neural Network (RNN) to automatically detect keyphrases from a document. We also used some preprocessing steps to clean and generate candidates keyphrases to train the model. Convolutional Neural Network can analyze semantic meanings of sentences. Bidirectional LSTM can learn the relations among words in the sentences. A Bengali pre-trained word embedding is used in this work.
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关键词
Keyphrase,Keyphrase Extraction,Keywords,BiL- STM,RNN,CNN,Convolutional Neural Network,Word Embedding,FastText,Neural Network
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