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Detect Professional Malicious User with Metric Learning in Recommender Systems. (arXiv:2205.09673v1 [cs.IR])
May 20, 2022, 1:12 a.m. | Yuanbo Xu, Yongjian Yang, En Wang, Fuzhen Zhuang, Hui Xiong
cs.LG updates on arXiv.org arxiv.org
In e-commerce, online retailers are usually suffering from professional
malicious users (PMUs), who utilize negative reviews and low ratings to their
consumed products on purpose to threaten the retailers for illegal profits.
Specifically, there are three challenges for PMU detection: 1) professional
malicious users do not conduct any abnormal or illegal interactions (they never
concurrently leave too many negative reviews and low ratings at the same time),
and they conduct masking strategies to disguise themselves. Therefore,
conventional outlier detection methods …
More from arxiv.org / cs.LG updates on arXiv.org
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