Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Generalized vector spaces model in information retrieval
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
The Wasabi Personal Shopper: a case-based recommender system
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Hybrid Hierarchical Knowledge Organization for Planning
EPIA '01 Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving
Acquiring Customer Preferences from Return-Set Selections
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
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This paper presents a knowledge-based product retrieval and recommendation system for e-commerce. The system is based on the observation that, in Business to Customer (B2C) e-commerce, customers' preferences naturally cluster into groups. Customers belonging to the same cluster have very similar preferences for product selection. The system is primarily based on product classification hierarchy. The hierarchy contains weight vectors. The system learns from experience. The learning is in the form of weight refinement based on customer selections. The learning resembles radioactive decay in some situations. Labor profile domain has been taken up for system implementation. The results are at the preliminary stage, and the system is not yet evaluated completely.