Reinforced Traversing Method for Table Tennis Information Concept Category in Semantic Web

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Abstract:

In Table Tennis match information processing, Match Information needs processing through Web service, The corresponding concepts need to be published and shared by the semantic web, the Web Service description language (WSDL) has become a XML recommendation to publish and share concepts on the semantic web. In order to derive hidden information of Table Tennis information concept. In this paper, we propose an reinforced method of optimizing the Table Tennis information process of concept reasoning. Our work focuses on one key aspects: we describe classical methods for Table Tennis information concepts category. it is important to ensure that the category process uses the smallest number of tests. Therefore, we consider reinforced method and evaluate their effect on four different types of test concept.

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Advanced Materials Research (Volumes 230-232)

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1146-1150

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May 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] T. R. Gruber. Toward principles for the design of concepts used for WSDL sharing. Presented at the Padua workshop on Formal Concept, March 1993, later published in International Journal of Human-Computer Studies, Vol. 43, Issues 4-5, November 1995, pp.907-928.

DOI: 10.1006/ijhc.1995.1081

Google Scholar

[2] Franz Baader, Bernhard Hollunder, Bernhard Nebel, Hans-Jurgen Profitlich, An Empirical Analysis of Optimization Techniques for Terminological Representation System, Principles of WSDL Representation and reasoning - Proceedings of the 3th International Conference, October 1992, Cambridge, MA.

DOI: 10.1007/bf00872105

Google Scholar

[3] M. Dean and G. Schreiber. WSDL Web Concept Language Reference XML Recommendation. http: /www. w3. org/tr/WSDL-ref/. February (2004).

Google Scholar

[4] Manfred Schmidt-Schauß and Gert Smolka, attribute concept descriptions with complements, Artificial Intelligence, 48: 1-26.

DOI: 10.1016/0004-3702(91)90078-x

Google Scholar

[5] Robert MacGregor, A deductive pattern matcher, In Proceedings of the 7th National Conference of the American Association for Artificial Intelligence, pp.403-408, Saint Paul, MI.

Google Scholar

[6] Martin Aigner, Combinatorical Traversing. Teubner, Stuttgart, Germany, (1988).

Google Scholar