2020
DOI: 10.1155/2020/8810817
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GFD: A Weighted Heterogeneous Graph Embedding Based Approach for Fraud Detection in Mobile Advertising

Abstract: Online mobile advertising plays a vital role in the mobile app ecosystem. The mobile advertising frauds caused by fraudulent clicks or other actions on advertisements are considered one of the most critical issues in mobile advertising systems. To combat the evolving mobile advertising frauds, machine learning methods have been successfully applied to identify advertising frauds in tabular data, distinguishing suspicious advertising fraud operation from normal one. However, such approaches may suffer from labo… Show more

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Cited by 12 publications
(1 citation statement)
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“…Network representation learning has also proven useful for fraud detection in insurance [27], mobile advertising [46], online fraud [47] and transaction fraud [48]. Despite these studies showing promising results, no studies have addressed the challenges associated with credit card fraud detection.…”
Section: Representation Learning In Graphsmentioning
confidence: 99%
“…Network representation learning has also proven useful for fraud detection in insurance [27], mobile advertising [46], online fraud [47] and transaction fraud [48]. Despite these studies showing promising results, no studies have addressed the challenges associated with credit card fraud detection.…”
Section: Representation Learning In Graphsmentioning
confidence: 99%