Customer Opinion from various E-commerce sitesusing Data Mining techniques: A Survey

Authors

  • Dutta PS Department of CSE, GirijanandaChowdhury Institute of Management & Technology
  • Saha A Department of CSE, GirijanandaChowdhury Institute of Management & Technology Hathkhowapara, Azara, Guwahati-
  • Sharma A Department of CSE, GirijanandaChowdhury Institute of Management & Technology Hathkhowapara, Azara, Guwahati-
  • Sarmah A Department of CSE, GirijanandaChowdhury Institute of Management & Technology Hathkhowapara, Azara, Guwahati-
  • Talukdar JK Department of CSE, GirijanandaChowdhury Institute of Management & Technology Hathkhowapara, Azara, Guwahati-

Keywords:

Optimized opinion, Quality, Sentiment

Abstract

With the availability of huge number of products, it became quite difficult for a customer to judge the quality about the product. Publicly available opinions are very important for decision making process. With the increasing number of reviews and comments for a particular product it became difficult to get an optimized opinion for that product. In this paper, we will study various reviews and the quality of the reviews from a huge number of positive and negative opinions on the product. All the reviews will be analysed on the basis of sentiment and will give a final opinion on the product. It will help every buyer to take a quick decision and gain a precise opinion for the products.

References

Zheng-Jun Zha, Member, IEEE, Jianxing Yu, Jinhui Tang, Member, IEEE, Meng Wang, Member, IEEE, and Tat-SengChua,Product Aspect Ranking and Its Applications.

GeorgLackermair, Daniel Kailer, KenanKanmaz, Importance of Online Product Reviews from a Consumer’s Perspective.

Minqing Hu and Bing Liu Department of Computer Science University of Illinois at Chicago, Mining and Summarizing Customer Reviews.

DrS Vijayarani, Ms J Ilamathi,Ms. Nithya,Preprocessing technique for text mining-An overview.

Theresa Wilson, JanyceWiebe, Paul Hoffmann, Recognizing Contextual Polarity in Phrase-level Sentiment analysis.

WalaaMedhat, Ahmed Hassan, HodaKorashy, Sentiment analysis algorithms and applications: A survey.

Lina L. Dhande, Dr. Prof. Girish K Patnaik,Analysing sentiments of movie review data using naïve bayes neural classifier.

ChetanKaushik and Atul Mishra Computer Engg. Department, YMCA University of Science & Technology, Faridabad, A Scalable, Lexicon Based Technique For Sentiment Analysis.

Ms. Gaurangi Patil1, Ms. Varsha Galande2, Mr. VedantKekan3, Ms. Kalpana Dange4, Sentiment Analysis Using Support Vector Machine.

Haiyang Sui,Christopher Khoo,Syin Chan, Sentiment Classification of Product Review using SVM and Decision Tree Induction.

Vijay Murari T 1, Sunil 2, Suchitra V3, Asst. Professor, Dept. of Computer Science, NMAMIT, Nitte, India, Survey on Product Recommendation Using Customer Reviews Based on Opinion Mining.

S. Chandra Kala and C. SindhuDepartment of Computer Science and Engineering, Velammal Engineering College, India, Opinion Mining and Sentiment Classification: A Survey.

Anascollomb, CrinaCostea, DamienJoyeux, OmarHasan, LionelBrunie,Study and Comparision of Sentiment Analysis methods for Reputation Evaluation.

MaiteTaboada,Julian Brooke, Milan Tofiloski, Kimberly Voll, Manfred Stede, Lexicon-Based Methods for Sentiment Analysis.

Downloads

Published

2025-11-11

How to Cite

[1]
P. S. Dutta, A. Saha, A. Sharma, A. Sarmah, and J. K. Talukdar, “Customer Opinion from various E-commerce sitesusing Data Mining techniques: A Survey”, Int. J. Comp. Sci. Eng., vol. 4, no. 7, pp. 58–61, Nov. 2025.

Issue

Vol. 4 No. 7 (2016): IJCSE Special Issue December Edition

Section

Survey Article

License

Creative Commons License

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

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.