GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Horting hatches an egg: a new graph-theoretic approach to collaborative filtering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Evaluation of Item-Based Top-N Recommendation Algorithms
Proceedings of the tenth international conference on Information and knowledge management
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
ACM Transactions on Information Systems (TOIS)
Hybrid Recommendation Approaches: Collaborative Filtering via Valuable Content Information
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences - Volume 08
Journal of Systems and Software
Feature-based recommendation system
Proceedings of the 14th ACM international conference on Information and knowledge management
Unifying user-based and item-based collaborative filtering approaches by similarity fusion
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A Comparison of Collaborative-Filtering Recommendation Algorithms for E-commerce
IEEE Intelligent Systems
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In this paper we present a preliminary work in which different rating based collaborative filtering algorithms are compared in terms of scalability and recommendation quality. Algorithms are tested using a reference database and results show that the selection of one or other algorithm depends on two factors: the scalability of the algorithms and the recommendation quality.