文章基本信息

标题：Shopping Site Recommendation Using Sentiment Analysis
本地全文：下载
作者：Kiran Salvi ; Vijay Pawar ; Pratik Kadu 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2016
卷号：4
期号：4
页码：6990
DOI：10.15680/IJIRCCE.2016.0404103
出版社：S&S Publications
摘要：Sentiment Analysis is to categories and identifies emotions defined in text for particular topic. Whether positive or negative. In Current Twitter Analysis system most of the people gives their opinion on different topic. In this system we use this concept for online shopping site. Now today, most of the people buy products from different online shopping sites and give the opinion about that product that is whether it is good or bad and also analyze what other people think about that product. In our propose d system we collect reviews from different sites and then categorize into positive or negative comment .After separation of comments then perform Sentiment Analysis on that reviews and recommend the best shopping site to the user. So this Experiment proves that proposed system are efficient and it is help full to the customer to save search time on all shopping site and also help full to customer to done their shopping efficiently.
关键词：positive; negative count; comments; reviews analysis