Interfacing thought: cognitive aspects of human-computer interaction
On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Experience with a learning personal assistant
Communications of the ACM
Communications of the ACM
A hybrid user model for news story classification
UM '99 Proceedings of the seventh international conference on User modeling
Selecting Examples for Partial Memory Learning
Machine Learning
The FindMe Approach to Assisted Browsing
IEEE Expert: Intelligent Systems and Their Applications
WWW Assisted Browsing by Reusing Past Navigations of a Group of Users
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
A Case-Based Reasoning Approach to Collaborative Filtering
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Similarity Measures for Structured Representations: A Definitional Approach
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Using user behaviour similarity for recommendation computation: the broadway approach
Proceedings of the HCI International '99 (the 8th International Conference on Human-Computer Interaction) on Human-Computer Interaction: Communication, Cooperation, and Application Design-Volume 2 - Volume 2
Categorizing Case-Base Maintenance: Dimensions and Directions
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Improved heterogeneous distance functions
Journal of Artificial Intelligence Research
Distributed Case-Based Reasoning for Fault Management
AIMS '07 Proceedings of the 1st international conference on Autonomous Infrastructure, Management and Security: Inter-Domain Management
Open-ended category learning for language acquisition
Connection Science - Language and Robots
Dimensions of Case-Based Reasoner Quality Management
ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Fault representation in case-based reasoning
DSOM'07 Proceedings of the Distributed systems: operations and management 18th IFIP/IEEE international conference on Managing virtualization of networks and services
Artificial Intelligence in Medicine
Case-based recommender systems: a unifying view
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
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Recommendations bysalesp eople are always based on knowledge about the products and expertise about your tastes, preferences, interests and behavior in the shop. In an attempt to model the behavior of salespeople, AI research has been focussed on the so called recommender agents. Such agents draw on previous results from machine learning and other advances in AI technologyto develop user models and to anticipate and predict user preferences. In this paper we introduce a new approach to recommendation, based on Case-Based Reasoning (CBR). CBR is a paradigm for learning and reasoning through experience, as salesmen do. We present a user model based on cases in which we try to capture both explicit interests (the user is asked for information) and implicit interests (captured from user interaction) of a user on a given item. Retrieval is based on a similarityfunction that is constantlytuned according to the user model. Moreover, in order to cope with the utility problem that current CBR system suffer from, our approach includes a forgetting mechanism (the drift attribute) that can be extended to other applications beyond e-commerce.