An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Similarity measure and instance selection for collaborative filtering
WWW '03 Proceedings of the 12th international conference on World Wide Web
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Mining user navigation patterns for personalizing topic directories
Proceedings of the 9th annual ACM international workshop on Web information and data management
Incremental Collaborative Filtering for Binary Ratings
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Improving Accuracy of Recommender System by Item Clustering
IEICE - Transactions on Information and Systems
Item-Based and User-Based Incremental Collaborative Filtering for Web Recommendations
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Incremental Learning of Triadic PLSA for Collaborative Filtering
AMT '09 Proceedings of the 5th International Conference on Active Media Technology
Incremental collaborative filtering via evolutionary co-clustering
Proceedings of the fourth ACM conference on Recommender systems
Web-based statistical fact checking of textual documents
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
A scalable tag-based recommender system for new users of the social web
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
Collaborative filtering on data streams
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Incremental Collaborative Filtering recommender based on Regularized Matrix Factorization
Knowledge-Based Systems
Alleviating the sparsity problem of collaborative filtering using trust inferences
iTrust'05 Proceedings of the Third international conference on Trust Management
Scalable collaborative filtering using incremental update and local link prediction
Proceedings of the 21st ACM international conference on Information and knowledge management
Rough Set Theory Based User Aware TV Program and Settings Recommender
International Journal of Advanced Pervasive and Ubiquitous Computing
International Journal of Advanced Pervasive and Ubiquitous Computing
Boosting the K-Nearest-Neighborhood based incremental collaborative filtering
Knowledge-Based Systems
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Most recommendation systems employ variations of Collaborative Filtering (CF) for formulating suggestions of items relevant to users' interests. However, CF requires expensive computations that grow polynomially with the number of users and items in the database. Methods proposed for handling this scalability problem and speeding up recommendation formulation are based on approximation mechanisms and, even when performance improves, they most of the time result in accuracy degradation. We propose a method for addressing the scalability problem based on incremental updates of user-to-user similarities. Our Incremental Collaborative Filtering (ICF) algorithm (i) is not based on any approximation method and gives the potential for high-quality recommendation formulation (ii) provides recommendations orders of magnitude faster than classic CF and thus, is suitable for online application.