Information filtering and information retrieval: two sides of the same coin?
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
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
A Case-Based Reasoning Approach to Collaborative Filtering
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Techniques and Knowledge Used for Adaptation During Case-Based Problem Solving
IEA/AIE '98 Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial In telligence and Expert Systems: Tasks and Methods in Applied Artificial Intelligence
Extendible Adaptive Hypermedia Courseware: Integrating Different Courses and Web Material
AH '00 Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
PTV: Intelligent Personalised TV Guides
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Personalised hypermedia presentation techniques for improving online customer relationships
The Knowledge Engineering Review
Tailoring and the Efficiency of Information Seeking
UM '07 Proceedings of the 11th international conference on User Modeling
AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques
The New Review of Hypermedia and Multimedia - Adaptive Hypermedia
Discussions on semantic-based in decision support systems
ECC'11 Proceedings of the 5th European conference on European computing conference
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In this paper, we present a new approach that is a synergy of item-based Collaborative Filtering (CF) and Case Based Reasoning (CBR) for personalized recommendations. We present a two-phase strategy: in phase I, we developed a context-sensitive item-based CF method that leverages the original past recommendations of peers via ratings performed on various information items. In phase II, we further personalize the information items comprising multiple components using a CBR-based compositional adaptation technique to selectively collect the most relevant information components and combine them into one composite recommendation. In this way, our approach allows fine-grained information filtering by operating at the constituent elements of an information item as opposed to the entire information item. We show that our strategy improves the quality and relevancy of the recommendations in terms of its appropriateness to the user’s needs and interests, and validated by statistical significance tests. We demonstrate the working of our strategy by recommending personalized music playlists.