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Reseach Article

Mining Online Reviews to Improve Sales Performance

Published on May 2016 by Rashmi Ghuge, Supriya Pawar, Pooja Balakrishna, Nilam Chavan, S.s. Shinde
National Conference on Advancements in Computer & Information Technology
Foundation of Computer Science USA
NCACIT2016 - Number 3
May 2016
Authors: Rashmi Ghuge, Supriya Pawar, Pooja Balakrishna, Nilam Chavan, S.s. Shinde
8e390cb0-363e-4f83-833e-8087586381d3

Rashmi Ghuge, Supriya Pawar, Pooja Balakrishna, Nilam Chavan, S.s. Shinde . Mining Online Reviews to Improve Sales Performance. National Conference on Advancements in Computer & Information Technology. NCACIT2016, 3 (May 2016), 14-17.

@article{
author = { Rashmi Ghuge, Supriya Pawar, Pooja Balakrishna, Nilam Chavan, S.s. Shinde },
title = { Mining Online Reviews to Improve Sales Performance },
journal = { National Conference on Advancements in Computer & Information Technology },
issue_date = { May 2016 },
volume = { NCACIT2016 },
number = { 3 },
month = { May },
year = { 2016 },
issn = 0975-8887,
pages = { 14-17 },
numpages = 4,
url = { /proceedings/ncacit2016/number3/24712-3049/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advancements in Computer & Information Technology
%A Rashmi Ghuge
%A Supriya Pawar
%A Pooja Balakrishna
%A Nilam Chavan
%A S.s. Shinde
%T Mining Online Reviews to Improve Sales Performance
%J National Conference on Advancements in Computer & Information Technology
%@ 0975-8887
%V NCACIT2016
%N 3
%P 14-17
%D 2016
%I International Journal of Computer Applications
Abstract

In Electronic commerce applications, the feedback ratings given by the customers are combined to calculate and assign seller's rating or their reputation trust score. The most widely used method in e-commerce applications to do this is via reputation trust models. But in such models the all good reputation problem is very commonly occurring, resulting in high trust scores or rating for all the sellers and this in turn makes it highly tricky for possible customers to select trustworthy and reliable sellers. In this paper, we propose a system for trust score calculation by mining feedback comments, on the basis of observation that the customers tend to express their views and opinions freely in the feedback comments section. The main objective is to implement a multidimensional trust model [1] for calculating the seller's reputation score from the information in the customer feedback comments and an algorithm for mining the text comments for dimension ratings and weights [1], using some techniques from natural language processing and from opinion mining [1] along with topic modelling. Comment based trust evaluation can successfully tackle the all good reputation problem and rank sellers efficiently, this has been revealed by previous experiments on eBay and Amazon data.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Electronic Commerce Text Mining Natural Language Processing Opinion Mining