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Discovery of Optimized Web Service Configurations Using a Hybrid Semantic and Statistical Approach

ARAN - Access to Research at NUI Galway

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dc.contributor.author Zaremba, Maciej en
dc.contributor.author Migdal, Jacek en
dc.contributor.author Hauswirth, Manfred en
dc.date.accessioned 2009-11-27T16:13:39Z en
dc.date.available 2009-11-27T16:13:39Z en
dc.date.issued 2009 en
dc.identifier.citation Maciej Zaremba, Jacek Migdal, Manfred Hauswirth "Discovery of Optimized Web Service Configurations Using a Hybrid Semantic and Statistical Approach", Proceedings of the IEEE 7th International Conference on Web Services (ICWS 2009), 2009. en
dc.identifier.uri http://hdl.handle.net/10379/445 en
dc.description.abstract We present a Semantic Optimized Service Discovery (Se- mOSD) approach capable of handling Web service search requests on a fine-grained level of detail where we augment semantic service descriptions with statistically built predictor functions. Our approach combines ontologies and mathematical functions built using statistical regression over previous Web service interactions. In the search requests we allow for arbitrary, independent and dependent constraints and user preferences expressed using objective functions. Our approach maps to standard Operational Research global optimization problem where algorithms of Simulated Annealing and Differential Evolution are used. It is capable of finding the optimal combination of service input and output parameters (a configuration) to a user re- quest with rich preferences. Our approach is applied to an international package shipment scenario where real (Web) services are used and mined to create price prediction models. We show that the chosen regression method provides price prediction models of high accuracy and our approach supports expressive and complex search requests. en
dc.format application/pdf en
dc.language.iso en en
dc.publisher IEEE en
dc.subject.lcsh Web services en
dc.title Discovery of Optimized Web Service Configurations Using a Hybrid Semantic and Statistical Approach en
dc.type Conference paper en
dc.local.publisherstatement ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. en
dc.description.peer-reviewed peer-reviewed en
dc.contributor.funder SUPER en
dc.contributor.funder Science Foundation Ireland en

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