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
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Ontological user profiling in recommender systems
ACM Transactions on Information Systems (TOIS)
A hybrid approach for searching in the semantic web
Proceedings of the 13th international conference on World Wide Web
Ontology-based personalized search and browsing
Web Intelligence and Agent Systems
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Web search personalization with ontological user profiles
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
What Have the Neighbours Ever Done for Us? A Collaborative Filtering Perspective
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
User profiles for personalized information access
The adaptive web
Collaborative filtering recommender systems
The adaptive web
Hybrid web recommender systems
The adaptive web
Information market based recommender systems fusion
Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Propagating user interests in ontology-based user model
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Applicability of recommender systems to medical surveillance systems
Proceedings of the second international workshop on Web science and information exchange in the medical web
Semi-automatic generation of recommendation processes and their GUIs
Proceedings of the 2013 international conference on Intelligent user interfaces
What to read next?: making personalized book recommendations for K-12 users
Proceedings of the 7th ACM conference on Recommender systems
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Collaborative recommendation is effective at representing a user's overall interests and tastes, and finding peer users that can provide good recommendations. However, it remains a challenge to make collaborative recommendation sensitive to a user's specific context and to the changing shape of user interests over time. Our approach to building context-sensitive collaborative recommendation is a hybrid one that incorporates semantic knowledge in the form of a domain ontology. User profiles are defined relative to the ontology, giving rise to an ontological user profile. In this paper, we describe how ontological user profiles are learned, incrementally updated, and used for collaborative recommendation. Using book rating data, we demonstrate that this recommendation algorithm offers improved coverage, diversity, personalization, and cold-start performance while at the same time enhancing recommendation accuracy.