Review Sentiment Analysis Based on Deep Learning

Zhongkai Hu, Jianqing Hu, Weifeng Ding, Xiaolin Zheng
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引用次数: 38

Abstract

With rapid development of E-commerce platforms, automated review sentiment analysis for commodities becomes a research focus, with main purpose to extract potential information within reviews for decision making of consumers. Traditional methods have made some progress on document level sentiment analysis, but with tremendous increasing of data scale, how to process high dimension of data fast and effectively becomes the largest limitation. In this paper, we import deep neural network which is appropriate for high dimension data analysis, and propose a framework of sentiment analysis based on deep learning. Experiments on different data scale and different domains show that the proposed method can solve high dimensional problem with good performance.
基于深度学习的评论情感分析
随着电子商务平台的快速发展,商品评论情感自动分析成为一个研究热点,其主要目的是提取评论中潜在的信息,供消费者决策。传统方法在文档级情感分析方面取得了一定的进展,但随着数据规模的急剧增加,如何快速有效地处理高维数据成为最大的限制。本文引入适合于高维数据分析的深度神经网络,提出了一种基于深度学习的情感分析框架。在不同数据规模和不同领域的实验表明,该方法能够有效地解决高维问题。
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