Classification and Blocking of Spam Users based on Review Using Expected Maximization Algorithm
Journal Title: Scholars Journal of Engineering and Technology - Year 2017, Vol 5, Issue 7
Abstract
An excellent source of collecting the reviews on specific product is various online shopping sites where people share their reviews on products and their shopping experience. People may come through the wrong opinions known as review spam. Therefore, for this it is essential to detect it by some means. In this paper, presents methods for detection of spam users using feature extraction and discretization, in combination with EM algorithm. Our framework can detect multiple spammers by knowing only small set of spammer sets. Proposed method effectively selects relevant features and builds features set to identify the spammers. In this paper, we have blocked the users with fake id or who are predicted as spammer. Keywords: Review spam, un-truthful reviews, opinion spam, rating spam.
Authors and Affiliations
Hema Dewangan, Om Prakash Dewangan, Toran Verma
Keywords
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