Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Fab: content-based, collaborative recommendation
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
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
Collaborative filtering with privacy via factor analysis
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Scalable collaborative filtering using cluster-based smoothing
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Time weight collaborative filtering
Proceedings of the 14th ACM international conference on Information and knowledge management
Improving Accuracy of Recommender System by Clustering Items Based on Stability of User Similarity
CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce
Google news personalization: scalable online collaborative filtering
Proceedings of the 16th international conference on World Wide Web
k-means++: the advantages of careful seeding
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
A framework for WWW user activity analysis based on user interest
Knowledge-Based Systems
Short communication: Recommendation based on rational inferences in collaborative filtering
Knowledge-Based Systems
It takes variety to make a world: diversification in recommender systems
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Collaborative filtering for orkut communities: discovery of user latent behavior
Proceedings of the 18th international conference on World wide web
Collaborative filtering adapted to recommender systems of e-learning
Knowledge-Based Systems
Adapting the right measures for K-means clustering
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Nearest-biclusters collaborative filtering with constant values
WebKDD'06 Proceedings of the 8th Knowledge discovery on the web international conference on Advances in web mining and web usage analysis
A new collaborative filtering metric that improves the behavior of recommender systems
Knowledge-Based Systems
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Y-Means: an autonomous clustering algorithm
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
SoS: um algoritmo para identificar pessoas homófilas em redes sociais com o uso da tradução cultural
Proceedings of the 11th Brazilian Symposium on Human Factors in Computing Systems
Preventing automatic user profiling in Web 2.0 applications
Knowledge-Based Systems
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The fast-growing popularity of online social communities and the massive amounts of user-generated content pose a critical need for, and new challenges on, content recommender system. The system needs to identify the unique and diverse interests of individual users and deliver content to interested users on a real-time basis. In this work, we propose Farseer, a system for personalized real-time content recommendation and delivery in online social communities. The proposed solution consists of a set of integrated offline and online algorithms that identify and utilize unique item-based interest clusters and cluster-based item rating in order to recommend newly-generated content items to individual users in real time. Our main contributions are (1) a detailed analysis of content popularity distribution and user interest distribution in online social communities; (2) a novel interest-based clustering and cluster-based content recommendation solution; and (3) a complete implementation and deployment in an online social community. Evaluation results gathered from real-world user studies demonstrate that the proposed system outperforms three widely-used collaborative filtering algorithms (kNN, PLSA, SVD) in existing recommender systems. It can effectively identify personal interests and improve the quality and efficiency of real-time personalized content recommendation in online social communities.