Authors
Huan Chen, Xin-Nan Li, Liang-Jie Zhang, Yi-Xuan Huang, Xiao-Sheng Cai
Publication date
2016/6/27
Conference
2016 IEEE International Congress on Big Data (BigData Congress)
Pages
236-243
Publisher
IEEE
Description
In modern society, Web gradually becomes the portal and window of all kinds of information. People are more likely to express their views on the Internet, mostly would be over the form of text documents. In order to understand users, NLP (Natural Language Processing) methods, such as sentiment analysis, have been gaining popularity. At present, there are some classical methods to solve the text sentiment analysis problem, such as the machine learning method, the classification models NB (Naive Bayes), ME (Maximum Entropy) and SVM (Support Vector Machine). In this paper, we mainly study sentiment analysis for big data scenarios from engineering perspective. This paper proposes core text processing services and discusses the corresponding development details. The contributions are manifolds: Firstly, a new core text processing service Cloud-based Core Text Processing Services (CCTPS) is proposed …
Total citations
2017201811
Scholar articles
H Chen, XN Li, LJ Zhang, YX Huang, XS Cai - 2016 IEEE International Congress on Big Data …, 2016