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AH
2008
Springer
14 years 2 months ago
Locally Adaptive Neighborhood Selection for Collaborative Filtering Recommendations
Abstract. User-to-user similarity is a fundamental component of Collaborative Filtering (CF) recommender systems. In user-to-user similarity the ratings assigned by two users to a ...
Linas Baltrunas, Francesco Ricci
WEBI
2009
Springer
14 years 2 months ago
Zero-Sum Reward and Punishment Collaborative Filtering Recommendation Algorithm
In this paper, we propose a novel memory-based collaborative filtering recommendation algorithm. Our algorithm use a new metric named influence weight, which is adjusted with ze...
Nan Li, Chunping Li
WEBI
2007
Springer
14 years 1 months ago
Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts
Collaborative filtering (CF) is one of the most successful approaches for recommendation. In this paper, we propose two hybrid CF algorithms, sequential mixture CF and joint mixtu...
Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaa...
UAI
2003
13 years 9 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...
ECWEB
2007
Springer
162views ECommerce» more  ECWEB 2007»
14 years 1 months ago
Impact of Relevance Measures on the Robustness and Accuracy of Collaborative Filtering
The open nature of collaborative recommender systems present a security problem. Attackers that cannot be readily distinguished from ordinary users may inject biased profiles, deg...
Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke