Effective review selection using micro reviews and feature level extraction
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 2
Abstract
The online review about the product helps the user to decide the quality of product or service. The task of identifying appropriate review and distill useful information to take decision is very difficult. The complication arises with unregulated, lengthy and redundant description in reviews. Micro reviews, arising trend to extract useful information from reviews in social networking. Micro reviews are small, focused and compact (in 200 characters long). In this paper, we proposed a methodology by using micro review as an objective to extract set of review content about the entity effectively. Here two methodologies is used as matching the review content with micro review and selecting set of reviews by using feature based opinion mining. The reviews get classified by using naive bayes algorithm to produce effective result. The evaluation gets performed in the data collected from foursquare and yelp.
Authors and Affiliations
A. Jenifaasheer, Dr. Anna Saro Vijendran
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