Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Communications of the ACM
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
Computer Methods for Mathematical Computations
Computer Methods for Mathematical Computations
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Applying Recursive CBR for the Custumization of Structured Products in an Electronic Shop
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Intelligent Sales Support with CBR
Case-Based Reasoning Technology, From Foundations to Applications
Ontology-Based Service Representation and Selection
IEEE Transactions on Knowledge and Data Engineering
Mediation of user models for enhanced personalization in recommender systems
User Modeling and User-Adapted Interaction
A Comparative Study of Reasoning Techniques for Service Selection
Agents and Peer-to-Peer Computing
Proceedings of the 20th ACM conference on Hypertext and hypermedia
Review: Personalizing recommendations for tourists
Telematics and Informatics
Re-using implicit knowledge in short-term information profiles for context-sensitive tasks
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Entertainment personalization mechanism through cross-domain user modeling
INTETAIN'05 Proceedings of the First international conference on Intelligent Technologies for Interactive Entertainment
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We introduce an application combining CBR and collaborative filtering techniques in the music domain. We describe a scenario in which a new kind of recommendation is required, which is capable of summarizing many recommendations in one suggestion. Our claim is that recommending one set of goods is different from recommending a single good many times. The paper illustrates how a case-based reasoning approach can provide an effective solution to this problem reducing the drawbacks related to the user profiles. CoCoA, a compilation compiler advisor, will be described as a running example of a collaborative case-based recommendation system.