A Study on the Review Classification Technique Using Micro Reviews
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 12
Abstract
Information mining in micro-blogging sites has been studied extensively; micro-reviews are a source of content that has been largely overlooked in the literature. In this paper micro-reviews, and can be used for the problem of review selection. To the best of our knowledge this is the first examine the micro reviews such as foursquare tips and combine them with full-text reviews such as Yelp reviews. Proposed work analyse the formulation of review selection, where the goal is to maximize coverage while ensuring efficiency, leading to coverage problems. The coverage problems are considered as broader interest, and they could find applications to different domains. The Proposed work consider approximation and heuristic algorithms, and study them experimentally, demonstrating quantitatively and qualitatively the benefits of the proposed approach. An Integer Linear Programming (ILP) formulation is also proposed, with provide an optimal algorithm. This allows us to quantify the approximation quality of the greedy heuristics. Experimental results explains the performance of the system against the State of art approach in terms of precision and Recall.
Authors and Affiliations
Dr. Anna Saro Vijendran, Miss. A. Jenifaasheer
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