AN INTEGRATED APPROACH FOR SUPERVISED LEARNING OF ONLINE USER REVIEWS USING OPINION MINING

被引：0
|
作者：
Shobana [1 ]
Leema, Anny [2 ]
机构：
[1] BS Abdur Rahman Univ, Dept Comp Sci & Engn, Madras 600100, Tamil Nadu, India
[2] BS Abdur Rahman Univ, Dept MCA, Madras 600100, Tamil Nadu, India
来源：
IIOAB JOURNAL | 2016年 / 7卷 / 09期
关键词：
Opinion Mining; Web Content; Mining; Sentiment Analysis; Naive Bayes;
D O I：
暂无
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
Internet is a place where people stores and shares information among the other entities reside in the network. In recent years, the amazing development of web technologies, lead to huge quantity of system and user generated information in online systems. This huge amount of information on web platforms enables them to use as data sources, in review making applications based on opinion mining and sentiment analysis. The paper put forward an algorithm for detecting sentiments on user reviews on movie, based on Naive Bayes classifier. We considered the opinion mining domain for the analysis of user reviews and the techniques used in sentimental analysis. We implemented the proposed algorithm to the user reviews and tested its performance, and suggested directions of development.
引用
收藏
页码：117 / 124
页数：8
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