A Review on Opinion Mining through Customer Experiences
|
10.5120/18854-0434 |
Nandini Burade and Ankita Kendhe. Article: A Review on Opinion Mining through Customer Experiences. International Journal of Computer Applications 107(18):37-39, December 2014. Full text available. BibTeX
@article{key:article,
author = {Nandini Burade and Ankita Kendhe},
title = {Article: A Review on Opinion Mining through Customer Experiences},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {107},
number = {18},
pages = {37-39},
month = {December},
note = {Full text available}
}
Abstract
Internet is fast growing and global system, which is most reliable and efficient. Now a day's social networking is increased due to which interaction of people with each other and share emotions, feedback, views, experiences, opinion and feedback about anything. Also the use of shopping sites i. e. online shopping is increasing tremendously and customers used to give their reviews and feedbacks, which are most important for buying or selling any product. But being as a customer it is difficult to read number of reviews every time while shopping. It leads to create confusion. So the technique which plays an important role in opinion mining and summering reviews of customer is data mining. Some existing techniques for opinion mining show only positive and negative comments from the customer reviews which is not efficient. The main aim of this article is to give an overall idea about the work done in past and about the proposed work.
References
- Jøsang, R. Ismail, and C. Boyd, A survey of trust and reputation systems for online service provision, 2007 DSS, vol. 43, no. 2, pp. 618–644, IEEE.
- Minqing H. , Bing L. ,Mining Opinion Features in Customer Reviews, Proceedings of the 19th national conference on Artificial intelligence Pages 755-760.
- B. Pang and L. Lee, Opinion mining and sentiment analysis Jan. 2008,vol. 2, no. 1–2, pp. 1–135,IEEE.
- Nitin J. , Bing L. , Identifying Comparative Sentences in Text Documents 2006, International ACM SIGIR Conference.
- Nitin J. , Bing L. , Mining Comparative Sentences and Relations, national conference on Artificial intelligence -Volume 2 Pages 1331-1336.
- Jiaming Z. , Han T. , Ying L. , Gather customer concerns from online product reviews– A text summarization approach March, 2009, International Journal Volume 36 Issue 2,. Pages 2107-2115.
- ZHU Jian, XU Chen, WANG Han-shi, Sentiment classification using the theory of ANNs, July 2010, The Journal of China Universities of Posts and Telecommunications, IEEE, 58–62.
- Long-Sheng Chen, Cheng-Hsiang Liu, Hui-Ju Chiu, A neural network based approach for sentiment classification in the blogosphere, 2011, IEEE.
- Shahab Saquib Sohail, Jamshed Siddiqui, Rashid Ali, User Feedback Scoring and Evaluation of a Product Recommendation System, IEEE, 2014.
- Sheng-Chin Yu, Fong-Ling Fu, Investigating Customer Needs and Evaluation Behavior in online shopping IEEE, 2010.
- Alisa Kongthon, Niran, Chatchawal Sangkeettrakarn, PornpimonPalingoon, ChoochartHaruechaiyasak, Using Opinion Mining Approach to Exploit Web Content in order to improve Customer Relationship Management, IEEE, 2010.
- Evgeny A. Stepanov, Giuseppe Riccardi, Detecting General Opinions from Customer Surveys, International Conference on Data Mining Workshop, IEEE, 2011.
- Raina Agrawal, Pradeep Y. , Bridging the Gap between Traditional and Online Shopping Methods for Indian Customers through Digital Interactive Experience, IEEE, 2013.
- Mansour Esmaeilpour, Vahideh Naderifar, Predict the customer behavior in the shopping by Distributed Learning Automata, IEEE, 2010.
- Ping Sun, Chunhui Wang, A Study of Factors Influencing Customers Online Shopping Behavior based on ANP, IEEE 2010.