基于LSTM递归神经网络的孟加拉语关键词提取

Nishat Tasnim Ahmed Meem, M. E. Chowdhury, Md. Mahfuzur Rahman
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引用次数: 1

摘要

关键字是描述该文件要点的单个或多个单词短语。这些关键字可以帮助读者了解文档的总体情况。本文提出了一种利用长短期记忆(LSTM)递归神经网络(RNN)从文档中自动检测关键短语的系统。我们还实现了多层感知器(MLP)网络来比较我们提出的LSTM方法的性能。我们在文档上应用了几个预处理步骤来生成候选关键短语。最后,我们发现与MLP网络相比,我们提出的方法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Keyphrase Extraction from Bengali Document using LSTM Recurrent Neural Network
Keyphrases are single or multiple word phrases of a document which portrays the principal points of that document. These keyphrases help readers to get an overview of the document. In this paper, we proposed a system that uses Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) to automatically detect keyphrases from a document. We also implemented Multilayer Perceptron (MLP) network to compare the performance of our proposed LSTM approach. We applied several pre-processing steps on a document to generate the candidate keyphrases. Finally, we found better performance from our proposed approach with compared to the MLP network.
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