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基于数据非随机缺失机制的推荐系统托攻击探测

DOI: 10.3724/SP.J.1004.2013.01681, PP. 1681-1690

Keywords: 协同过滤,托攻击,缺失数据,Dirichlet过程,变分推断

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Abstract:

?协同过滤推荐系统极易受到托攻击的侵害.开发托攻击探测技术已成为保障推荐系统可靠性与鲁棒性的关键.本文以数据非随机缺失机制为依托,对导致评分缺失的潜在因素进行解析,并在概率产生模型框架内将这些潜在因素与Dirichlet过程相融合,提出了用于托攻击探测的缺失评分潜在因素分析(Latentfactoranalysisformissingratings,LFAMR)模型.实验表明,与现有探测技术相比,LFAMR具备更强的普适性和无监督性,即使缺乏系统相关先验知识,仍可有效探测各种常见托攻击.

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