A System for Principled Matchmaking in an Electronic Marketplace
International Journal of Electronic Commerce
A Software Framework for Matchmaking Based on Semantic Web Technology
International Journal of Electronic Commerce
Logic-based automated multi-issue bilateral negotiation in peer-to-peer e-marketplaces
Autonomous Agents and Multi-Agent Systems
Fuzzy matchmaking in e-marketplaces of peer entities using Datalog
Fuzzy Sets and Systems
A Nonmonotonic Approach to Semantic Matchmaking and Request Refinement in E-Marketplaces
International Journal of Electronic Commerce
Weighted Description Logics Preference Formulas for Multiattribute Negotiation
SUM '09 Proceedings of the 3rd International Conference on Scalable Uncertainty Management
Semantic matchmaking as non-monotonic reasoning: a description logic approach
Journal of Artificial Intelligence Research
Computing Information Minimal Match Explanations for Logic-Based Matchmaking
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
A Unified Framework for Non-standard Reasoning Services in Description Logics
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Computing utility from weighted description logic preference formulas
DALT'09 Proceedings of the 7th international conference on Declarative Agent Languages and Technologies
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Matchmaking can be basically seen as the process of computing a ranked list of resources with respect to a given query. Semanticmatchmaking can be hence described as the process of computing such ordered list also taking into account the semantics of resources description and of the query, provided with reference to a logic theory (an ontology, a set of rules, etc.) [3]. A matchmaking step is fundamental in a number of retrieval scenarios spanning from (Web) service discovery and composition to e-commerce transactions up to recruitment in human resource management for task assignment, just to cite a few of them. Also in interactive exploratory tasks, matchmaking and ranking play a fundamental role in the selection of relevant resources to be presented to the user and, in case, further explored. In all the above mentioned frameworks, the user query may contain only hard (strict) requirements or may represent also her preferences. We will see how to handle both cases while computing the ranked list of most promising resources.