Identify of Ranking Problems and Fraud for Mobile apps

Abstract

We take new methods and techniques used for the finding the position of rankings in various mobile applications. Rankings play is major role in mobile applications and other products. Customers take applications depended on the ranking and also by reading the review and rating given to it Positioning extortion in the portable App market alludes to misleading changes with the  reason for knocking up the Apps in the ubiquity list. It turns out to be more successive for App deplovementto uses shady means, The proposed model mines the leading sessions of mobile apps to precisely locate the ranking imposture. Additionally system finds ranking, rating and review process and investigation of different evidences, Theranking based evidences rating based evidences and review based evidences is done. We propose an optimization depend aggregation model to integrate all the evidences for position imposture. We findingthe proposed model with real-world App data aggressions from the Apple’s App Store for a long time period. Fuzzy Logic is uses many valued logic which produces the true value of variables. From the collected dataset input is fuzzy filed into member function. Rules isexecuted with input values to produce fuzzy output. Map a fuzzy output member functions into crisp output results which is used for position. Fuzzy model produces the true value for position of imposture ranking. Works well for large amount of data in order to increase the scalability.