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About Discovery of Ranking Fraud For Mobile Apps
This document proposes a system for detecting ranking fraud for mobile apps. It identifies three key challenges: (1) fraud does not always occur, so the system must detect local rather than global anomalies, (2) the large number of apps requires scalable automatic detection without benchmarks, and (3) dynamic rankings make evidence linking difficult. The system addresses these by mining app leading sessions to focus detection, investigating ranking, rating and review evidence through statistical tests, and optimally aggregating evidence for detection. An evaluation on real iOS app data validated the system's effectiveness and scalability.
Detailed Information
| Author: | ['gopi'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 14 |
| Language: | English |
| Format: | |
| Price: | FREE |
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