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» Explaining collaborative filtering recommendations
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COOPIS
2004
IEEE
13 years 11 months ago
Paradigms for Decentralized Social Filtering Exploiting Trust Network Structure
Recommender systems, notably collaborative and hybrid information filtering approaches, vitally depend on neighborhood formation, i.e., selecting small subsets of most relevant pee...
Cai-Nicolas Ziegler, Georg Lausen
ICDM
2005
IEEE
126views Data Mining» more  ICDM 2005»
14 years 1 months ago
Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems
Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. Researchers have shown that attackers can manipulate a system’s reco...
Robin D. Burke, Bamshad Mobasher, Runa Bhaumik, Ch...
ICCBR
1999
Springer
14 years 2 days ago
Surfing the Digital Wave
In the future digital TV will offer an unprecedented level of programme choice. We are told that this will lead to dramatic increases in viewer satisfaction as all viewing tastes a...
Barry Smyth, Paul Cotter
AICS
2009
13 years 5 months ago
Robustness Analysis of Model-Based Collaborative Filtering Systems
Collaborative filtering (CF) recommender systems are very popular and successful in commercial application fields. However, robustness analysis research has shown that conventional...
Zunping Cheng, Neil Hurley
ACMSE
2006
ACM
14 years 1 months ago
Support vector machines for collaborative filtering
Support Vector Machines (SVMs) have successfully shown efficiencies in many areas such as text categorization. Although recommendation systems share many similarities with text ca...
Zhonghang Xia, Yulin Dong, Guangming Xing