Learning maximal structure rules in fuzzy logic for knowledge acquisition in expert systems
Fuzzy Sets and Systems
Cooperative vs. Competitive Multi-Agent Negotiations in Retail Electronic Commerce
CIA '98 Proceedings of the Second International Workshop on Cooperative Information Agents II, Learning, Mobility and Electronic Commerce for Information Discovery on the Internet
Acquiring domain knowledge for negotiating agents: a case of study
International Journal of Human-Computer Studies
Using fuzzy repertory table-based technique for decision support
Decision Support Systems
IEEE Transactions on Fuzzy Systems
A Recommender System Based on a Machine Learning Algorithm for B2C Portals
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
A highly adaptive recommender system based on fuzzy logic for B2C e-commerce portals
Expert Systems with Applications: An International Journal
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Machine learning algorithms can be used to discover patterns in data into e-commerce C2C portals and this knowledge can then be useful to help customers to refine their searches and to choose what to buy. In this work, it is proposed a new machine learning algorithm based on fuzzy logic. We describe the proposed algorithm for supporting customer searches in e-Marketplaces and show the results obtained on simulated examples.