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Semantic Matchmaking Algorithm

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Semantic Matchmaking Algorithm. Marko Lazi ć 3335/2011 marko.lazi c 88@gmail.com. Department of Computer Engineering and Computer Science, School of Electrical Engineering, University of Belgrade. /10. Introduction .

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Semantic Matchmaking Algorithm
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  1. Semantic Matchmaking Algorithm Marko Lazić 3335/2011 marko.lazic88@gmail.com Department of Computer Engineering and Computer Science, School of Electrical Engineering, University of Belgrade

  2. /10 Introduction • The ability to dynamically discover and invoke a Web Service is a critical aspect of Service Oriented Architectures • In order to overcome the limitations of a syntax-based search, matchmaking algorithms • originally proposed by M. Paolucci

  3. /10 Algorithm • The algorithm takes a OWL-S Query from the client as input • Iterates over every OWL-S Advertisement in its repository in order to determine a match • An Advertisement and a Query match if their Outputs and Inputs match • The algorithm returns a set of matching advertisements sorted according to the degree of match

  4. /10 Algorithm(2) • Let Queryout and Advtout represent the list of output concepts of the Query and Advertisement respectively • Matching the outputs requires the matching between two concept-lists, Queryout and Advtout

  5. /10 Algorithm(3) • Let Queryin and Advtin represent the list of input Concepts of the Query and Advertisement respectively. • Matching the inputs requires:

  6. /10 Degrees of match (1) • Four degrees of match are defined between a them: • Exact: • If outA is an equivalent concept to outQ oroutA is a superclass of outQ • In case of a superclass relationship, it is assumed that the service provider has agreed to support every possible subclass of outA • Plugin: • If outA Subsumes outQ • The relation between outA and outR is weaker as compared to the previous case since subsumption is indirectly inferred by the reasoner • It is assumed that the provider has agreed to support some sub-concepts of outA • We hence infer that outA can be plugged in place of the required outR

  7. /10 Degrees of match (2) • Subsume • If outQ Subsumes outA • The set of individuals defined by the concept, outA, is a subset of the set of individuals defined by the concept outR • Fail: If none of the above conditions are satisfied

  8. /10 Conclusion • outcome of the matchmaker depends on the order of the concepts in the Query • Semantic matchmaking should be agnostic of the syntactic ordering of the concepts in the Advertisements and Queries • instead of the greedy approach adopted by this algorithm there could be made better approach

  9. /10 References • [1] JENA: Java Framework for Building Semantic Web Applications. http://jena.sourceforge.net/. • [2] MINDSWAP: Maryland Information and Network Dynamics Lab Semantic Web Agents Project, OWL-S API. http://www.mindswap.org/2004/owl-s/api/. • [3] North American Industry Classification System. http://www.naics.com/. • [4] OWL-S Service Retrieval Test Collection. Version 2.1. http://projects.semwebcentral.org/projects/owls-tc/. • [5] Pellet: An OWL DL Reasoner. http://pellet.owldl.com/. • [6] Protege: Ontology Editor and Knowledge-base framework. http://protege.stanford.edu/. • [7] RacerPro: OWL Reasoner and Inference Server for the Semantic Web. http://www.racer-systems.com/. • [8] Universal Description Discovery and Integration (UDDI). http://uddi.org/.

  10. /10 Questions? Marko Lazić(marko.lazic88@gmail.com) Department of Computer Engineering and Computer Science, School of Electrical Engineering, University of Belgrade