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篇名 |
Recommendation System to Identify Collusive Users in Online Auctions Using the Pollution Diffusion Method
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並列篇名 | Recommendation System to Identify Collusive Users in Online Auctions Using the Pollution Diffusion Method |
作者 | 鄭辰仰、Iuon-Chang Lin、Hao-Ju Wu |
英文摘要 | Reputation systems provide mechanisms for differentiating between honest and dishonest participants in ecommerce environments. Several reputation systems are deployed in practical electronic marketplaces. However, a considerable challenge is that malicious groups may unlawfully increase their reputation through deceitful manipulation of purchase feedback. Therefore, reputation systems must be robust and able to detect collusion, deception, and strategic manipulation. This study proposes a recommendation system to identify collusive users, inspired by observing the spread of pollution. After identifying malicious users, the suspects are likely to be identified using the proposed scheme, which efficiently reduces the relationship network size by removing relationships with positive ratings. According to the simulation results, pollution diffusion took 16 ms in a simulation involving 5000 users. |
起訖頁 | 353-358 |
關鍵詞 | Recommendation systems、Reputation systems、Purchase feedback、Collusion、Online auctions |
刊名 | 網際網路技術學刊 |
期數 | 201903 (20:2期) |
出版單位 | 台灣學術網路管理委員會 |
DOI |
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