文章基本信息

标题：Analysis of Various Opinion Mining Algorithms
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作者：Gayathri R Krishna ; Kavitha S ; Yamini S 等
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2015
卷号：22
期号：2
页码：72-75
DOI：10.14445/22312803/IJCTT-V22P114
出版社：Seventh Sense Research Group
摘要：Online reviews, blogs, and discussion forums such as WebMD on chronic diseases and medicines are becoming important supporting resources for patients. Extracting useful information from these substantial bodies is very difficult and challenging. Opinion mining or sentiment analysis involves the extraction of useful information (e.g., positive or negative sentiments of a product) from a large quantity of text opinions or reviews authored by Internet users. Various algorithms had been proposed to extract information from the opinion of internet users. Some of the algorithms are LDA, sLDA, NMF, SSNMF, DiscLDA and PAAM. In this paper, we are discussing and analysing these opinion mining algorithms.
关键词：Opinion mining; text mining; topic modelling; aspectmining.