Title :
Review Sentiment Analysis Based on Deep Learning
Author :
Zhongkai Hu;Jianqing Hu;Weifeng Ding;Xiaolin Zheng
Author_Institution :
Coll. of Comput. Sci., Zhejiang Univ., Hangzhou, China
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.
Keywords :
"Feature extraction","Sentiment analysis","Machine learning","Context","Neural networks","Semantics","Algorithm design and analysis"
Conference_Titel :
e-Business Engineering (ICEBE), 2015 IEEE 12th International Conference on
DOI :
10.1109/ICEBE.2015.24