Classifying product reviews from balanced datasets for Sentiment Analysis and Opinion Mining

被引：2
作者：
Sudhakaran, Periakaruppan [1 ]
Hariharan, Shanmugasundaram [2 ]
Lu, Joan [3 ]
机构：
[1] Oxford Engn Coll, Tiruchirappalli, Tamil Nadu, India
[2] TRP Engn Coll, Irungalur, Tamil Nadu, India
[3] Univ Huddersfield, Huddersfield HD1 3DH, W Yorkshire, England
来源：
2014 6TH INTERNATIONAL CONFERENCE ON MULTIMEDIA, COMPUTER GRAPHICS AND BROADCASTING (MULGRAB) | 2014年
关键词：
D O I：
10.1109/MulGraB.2014.14
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
The Online reviews provided for a product enables web user to make decisions appropriately. These reviews may be positive, negative or neutral in nature. Analyzing and classifying such product reviews have attracted reasonable interest. It has become quite hard to make decisions since we aren't able to obtain the decisions quickly. Hence it is required to classify the reviews from balanced data sets for analysis and opinion mining of any applications. The reason for considering balanced data sets is that the decision will not be biased on the category of reviews considered. We have carried out investigations using similarity measures to categorize the reviews correctly. Experiments reveal that the reviews that were mixed in nature were able to be grouped correctly.
引用
收藏
页码：29 / 34
页数：6
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