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Utilizing Support Vector Machines in Mining Online Customer Reviews

Research Authors
Taysir Hassan A. Soliman, Mostafa A. Elmasry, Abdel Rahman Hedar, and Magdy M. Doss
Research Department
Research Journal
Proceedings of 22th International Conference on Computer Theory and Applications ICCTA 2012, Alexandria, Egypt
Research Rank
4
Research Publisher
NULL
Research Vol
NULL
Research Website
-
Research Year
2012
Research_Pages
NULL
Research Abstract

As e-commerce is increasingly becoming popular, the
number of customer reviews that a product receives grows
rapidly. However, for popular products, many online product
reviews exist but for other reviews product reviews are very few. These online discussions about particular products may help other online users to make a decision in buying/ not buying those products, like in amazon.com and ebay.com. Since an enormous number of unstructured and ungrammatical reviews on a product exist, opinion mining is getting a crucial research area for better decision making of buying products. In this paper, we apply an opinion mining approach to summarize the unstructured and ungrammatical users' reviews, based on Support Vector Machine (SVM). Two levels of classification is applied: 1)Features classification and 2) Polarity classification
for every feature class. Our approach has been tested on Amazon data with dataset of 535 sentences, where a summary is obtained and analysis of precision (93.15%) and recall (92.41%) illustrate the accuracy of the proposed system.