Title :
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
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;
Conference_Titel :
Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-6817-6
DOI :
10.1109/ICIIECS.2015.7193034
