IDENTIFYING RATING AND REVIEW BASED RANKING FRAUD IN MOBILE APP MARKET

Abstract

Nowadays ranking fraud in mobile App market became more popular in the market in order to display their
apps in the popularity list and to boost their sales.As the applications increase the fraud is also increasing.
Therefore, there will be an increase in ranking fraud in the upcoming time, as the number of Apps developers
and applications will likely grow very significantly. Many traditional methods of fraud analysis have been used
to detect fraud. But these methods are complex and time-consuming. However, there is more need to adopt
some better techniques which can ensure the ranking fraud detection efficiently by data mining analysis. This
paper explores the data mining methods to identify the fraud by using Rank Aggregation algorithm. Further
three types of proofs are studied they are ranking, rating and user comment proofs. And an aggregation method
is used to aggregate all the proofs and will produce an optimized report for fraud detection.