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使用深度学习方法对IMDB电影评价做情感分析,使用的方法分别为:MLP、BiRNN、BiGRU+Attention Model

Python 100.00%

sentiment_analysis's Introduction

情感分析(Sentiment analysis)是自然语言处理(NLP)领域的一个任务,又称倾向性分析,意见抽取(Opinion extraction),
意见挖掘(Opinion mining),情感挖掘(Sentiment mining),主观分析(Subjectivity analysis)等,它是对带有情感色彩的主观性文本进行
分析、处理、归纳和推理的过程,如从电影评论中分析用户对电影的评价(positive、negative),从商品评论文本中分析用户对商品的“价格、大小、
重量、易用性”等属性的情感倾向。

本项目采用三种深度学习方法对IMDB评论进行情感分析。这三种方法为:MLP、BiRNN(LSTM、GRU)、BiGRU+Attention。
使用的深度学习框架是Keras,后端是TensorFlow,在GPU服务器上运行,GPU服务器型号是TITAN X。

详情见我的博客(http://blog.csdn.net/mpk_no1/article/details/71698725)

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