A Survey on Sentimental Analysis of Online Product Reviews for Various E-Shopping Websites

Authors

  • Punitha Devi C  Professor, Department Of Information Technology, Sri Manakula Vinayagar Engineering College, Puducherry, India
  • Vijayalalitha V  B.Tech, Department Of Information Technology, Sri Manakula Vinayagar Engineering College, Puducherry, India
  • Raja Rajeswari S  B.Tech, Department Of Information Technology, Sri Manakula Vinayagar Engineering College, Puducherry, India
  • Lendaa V  B.Tech, Department Of Information Technology, Sri Manakula Vinayagar Engineering College, Puducherry, India

Keywords:

QD Miner, Sentiment Analysis, Product Reviews, E-Shopping Websites, Review Analysis

Abstract

The rapid growth of internet is a wide source of learning and decision making. Thousands of reviews are generated each day for the online products. Analyses of these opinions are very important because it is helpful in determining the users’ perspective about the product and also for making business decisions in the organizations. The sentiment analysis system is build on the basis of identifying the words and classifying its sentiments from the e-shopping websites using data mining approach. The proposed system selects the words from the learning dataset and then classifies them into objects and sentiments based on a feature extraction methodology. A Quality Data miner technique has been adapted to study about the polarity of the each review in both sentence and aspect level. A featured specific comparison has been made with the results that are retrieved using the QD technique and the product with the desired feature has been recommended to the user. The QD miner technique is able to classify user opinions with good precision and accuracy.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Punitha Devi C, Vijayalalitha V, Raja Rajeswari S, Lendaa V, " A Survey on Sentimental Analysis of Online Product Reviews for Various E-Shopping Websites, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.593-598, March-April-2018.