Ranking Fraud Detection System and Recommendation System for Mobile Apps

Ranking fraud in the mobile Apps is nothing but the false or fake activities which are going to be done in Apps popularity list for bumping up the fraud App . It is very easy for the App developer to use the fake App and fake rating for commiting the ranking fraud . The research in ranking fraud of the mobile App is limited . For that purpose a ranking fraud detection system and the App recommendation system is proposed . There are mainly three types of evidences , Ranking based evidences , Rating based evidences , and Review based evidences . These evidences can be obtained from Apps ranking , rating and review history .Then proposed an optimization based aggregation method for integrating all these evidences for the fraud detection .In this way more effectiveness and regularity of the ranking fraud detection system is obtained and the original App is recommended to the user.