Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Larks: Dynamic Matchmaking Among Heterogeneous Software Agents in Cyberspace
Autonomous Agents and Multi-Agent Systems
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources
IEEE Transactions on Knowledge and Data Engineering
Asymptotic behaviors of support vector machines with Gaussian kernel
Neural Computation
Translating owl and semantic web rules into prolog: Moving toward description logic programs
Theory and Practice of Logic Programming
Deployed Semantic Services for the Common User of the Web: A Reality Check
ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
OWLS-MX: A hybrid Semantic Web service matchmaker for OWL-S services
Web Semantics: Science, Services and Agents on the World Wide Web
Hybrid Adaptive Web Service Selection with SAWSDL-MX and WSDL-Analyzer
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Generalization of clauses under implication
Journal of Artificial Intelligence Research
Electronic Commerce Research and Applications
The creation and evaluation of iSPARQL strategies for matchmaking
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
iSeM: Approximated Reasoning for Adaptive Hybrid Selection of Semantic Services
ICSC '10 Proceedings of the 2010 IEEE Fourth International Conference on Semantic Computing
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
A survey of fuzzy service matching approaches in the context of on-the-fly computing
Proceedings of the 16th International ACM Sigsoft symposium on Component-based software engineering
Fuzzy service matching in on-the-fly computing
Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering
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We present iSeM (intelligent Service Matchmaker), a precise hybrid and adaptive matchmaker for semantic Web services, which exploits functional service descriptions in terms of logical signature annotations as well as specifications of preconditions and effects. In particular, besides well-known strict logical matching filters and non-logic-based textual and structural signature matching, it adopts approximated reasoning based on logical concept abduction and contraction for the description logic subset SH with information-theoretic valuation for matching inputs and outputs. In addition, it uses a stateless logical specification matching approach, which applies the incomplete but decidable@q-subsumption algorithm for preconditions and effects. The optimal aggregation strategy of all those aspects is learned off-line by means of a binary SVM-based service relevance classifier in combination with evidential coherence-based pruning to improve ranking precision with respect to false classification of any such variant on its own. We demonstrate the additional benefit of the presented approximation and the adaptive hybrid combination by example and by presenting an experimental performance analysis.