Prevention of Online Fake Voting with Collaborative Filtering Techniques

SreeDevi M, Haritha Paladugu, Ravali K

Abstract


Social voting engine has risen as a significant in online social networking sites. Various online social networking sites provide voting as well as opinion facility. Social voting includes opinions of various and different viewers on various and different set of products that are available online respectively. Now-a-days E-commerce and commercial sites are getting benefited a lot by using these online social voting systems. By voting system we can able to identify the scalability, sustainability and performance of any item in the online market. Due to rapid growth of internet usage many votes for any item can be emerged. It has developed various unique challenges and opportunities for recommendation systems. Information about the items and the viewer’s got overloaded because of availability of large data sets which are generated from the queries that are stated by the viewer about the item or product in the market. To overcome fake voting’s, we considered collaborative filtering method. In this paper, we proposed a recommendation system that recommends items using matrix factorization and nearest-neighbour methods.


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