Association data mining in Sentiment Analysis

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-39 Number-2
Year of Publication : 2016
Authors : Mr. Rajendra Gawali, Ms. Prajacta Lobo
  10.14445/22312803/IJCTT-V39P115

MLA

Mr. Rajendra Gawali, Ms. Prajacta Lobo "Association data mining in Sentiment Analysis". International Journal of Computer Trends and Technology (IJCTT) V39(2):83-88, September 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Prior to making a purchase, an online shopper typically browses through several similar products of different brands before reaching a final decision. This will help buyer to make better decisions based on reviews provided by previous customer. Reviews can be positive, negative or neutral. These review data available online in multiple formats with huge volume, thus identifying this sentiment is very important. Analysing this data manually is very time consuming as well as erroneous. Our focus here is extracting efficient or relevant wards from review data, sentiment polarity classification, learning and comparing algorithm in finding frequent itemset.

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Keywords
Sentiment analysis, association data mining, frequent itemset, FP-Tree.