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@article{144038,
        author = {LUNAVATH HARITHA and M.OMPRAKASH},
        title = {Ranked Fraud Detection for Mobile Apps},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {5},
        pages = {188-191},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144038},
        abstract = {The number of mobile Apps has grown at enormous price during the last few decades. Ranking fraud in the mobile App market refers to fraudulent or fake pursuits which have a rationale of striking up the Apps within the fame record. It makes usual for App developers to post fake App ratings, to commit ranking fraud. Even as the value of stopping ranking fraud has been generally recognized, there's constrained understanding and study in this discipline. To this end, in this paper, we provide a quick view of ranking fraud and advise a ranking fraud detection process for mobile Apps. Mainly, we first endorse to safely locate the ranking fraud through mining the lively durations through utilizing mining leading session algorithm. Additionally, we investigate three varieties of evidences, i.e., ranking based evidences, score based evidences and overview based evidences, by way of finding out ancient records. We used an surest aggregation system to integrate all the evidences for fraud detection.},
        keywords = {Mobile Apps, Ranking Fraud Detection, Evidence Aggregation, Historical Ranking Records.},
        month = {},
        }