Review analyzer analysis of product reviews on WEKA classifiers

Author

Kshirsagar, Aditya A. ; Deshkar, Prarthana A.

Author_Institution

Dept. of Comput. Technol., Yeshwantrao Chavan Coll. of Eng., Nagpur, India

fYear

2015

Firstpage

1

Lastpage

5

Abstract

E-transactions have become promising and very much convenient due to worldwide and usage of the internet. The consumer reviews are increasing rapidly in number on various products. These large numbers of reviews are beneficial to manufacturers and consumers alike. It is a big task for a potential consumer to read all reviews to make a good decision of purchasing. It is beneficial to mine available consumer reviews for popular products from various product review sites of consumer. The first step is performing sentiment analysis to decide the polarity of a review. On the basis of polarity, we can then classify the review. Comparison is made among the different WEKA classifiers in the form of charts and graphs.

Keywords

Internet; data mining; graph theory; learning (artificial intelligence); Internet; WEKA classifiers; Waikato Environment for Knowledge Analysis; e-transactions; Accuracy; Classification algorithms; Conferences; Crawlers; Data mining; Feature extraction; Sentiment analysis; Online Reviews; Polarity of Reviews; WEKA Classifier;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on

Conference_Location

Coimbatore

Print_ISBN

978-1-4799-6817-6

Type

conf

DOI

10.1109/ICIIECS.2015.7193034

Filename

7193034