An Improved Mobile Rank Fraud Detection with Leading Sessions and Review Analysis
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2017 by IJETT Journal|
|Year of Publication : 2017|
|Authors : V.Aswini, N. Swaroop, Dr.C.P.V.N.J Mohan Rao
V.Aswini, N. Swaroop, Dr.C.P.V.N.J Mohan Rao "An Improved Mobile Rank Fraud Detection with Leading Sessions and Review Analysis", International Journal of Engineering Trends and Technology (IJETT), V48(2),74-77 June 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Recognition of rank oriented results for products is highly hard issue in the base of data and knowledge engineering. It is because of various tools and programs are there to introduce the fake ranking products. It leads to incorrect raking of products even though they are not. In the detail analysis of ranking records, the results came to know that apps ranking behaviors is in a top position and always satisfy a particular ranking pattern. It contains various ranking steps such as ranking, rising, maintaining and recession. In leading process ranking increases the highest position in the dashboard. Based on the various raking events we studied so many patterns of ranking. We propose a novel idea of rank implementation with session recognition and decreases the fake ranking and comments over the apps and products and our work results best compared to traditional approaches and give accurate results.
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We propose a novel idea of rank implementation with session recognition and decreases the fake ranking and comments over the apps and products and our work results best compared to traditional approaches and give accurate results.