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ICDM
2008
IEEE
183views Data Mining» more  ICDM 2008»
14 years 2 months ago
Collaborative Filtering for Implicit Feedback Datasets
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track differe...
Yifan Hu, Yehuda Koren, Chris Volinsky
ICDM
2005
IEEE
168views Data Mining» more  ICDM 2005»
14 years 1 months ago
Usage-Based PageRank for Web Personalization
Recommendation algorithms aim at proposing “next” pages to a user based on her current visit and the past users’ navigational patterns. In the vast majority of related algor...
Magdalini Eirinaki, Michalis Vazirgiannis
ICCBR
2005
Springer
14 years 1 months ago
Re-using Implicit Knowledge in Short-Term Information Profiles for Context-Sensitive Tasks
Typically, case-based recommender systems recommend single items to the on-line customer. In this paper we introduce the idea of recommending a user-defined collection of items whe...
Conor Hayes, Paolo Avesani, Emiliano Baldo, Padrai...
EWCBR
2004
Springer
14 years 1 months ago
Dynamic Critiquing
Abstract. Critiquing is a powerful style of feedback for case-based recommender systems. Instead of providing detailed feature values, users indicate a directional preference for a...
James Reilly, Kevin McCarthy, Lorraine McGinty, Ba...
ICDM
2003
IEEE
142views Data Mining» more  ICDM 2003»
14 years 28 days ago
Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques
Collaborative Filtering (CF) techniques are becoming increasingly popular with the evolution of the Internet. E-commerce sites use CF systems to suggest products to customers base...
Huseyin Polat, Wenliang Du