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Association search in semantic web: search + inference

Published:10 May 2005Publication History

ABSTRACT

Association search is to search for certain instances in semantic web and then make inferences from and about the instances we have found. In this paper, we propose the problem of association search and our preliminary solution for it using Bayesian network. We first minutely define the association search and its categorization. We then define tasks in association search. In terms of Bayesian network, we take ontology taxonomy as network structure in Bayesian network. We use the query log of instances to estimate the network parameters. After the Bayesian network is constructed, we give the solution for association search in the network.

References

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  2. Ding, L., Finin, T.W., Joshi, A., Pan, R., Scott Cost, R., Peng, Y., Reddivari, P., Doshi, V., Sachs, J.: Swoogle: a search and metadata engine for the semantic web. CIKM 2004: 652--659 Google ScholarGoogle ScholarDigital LibraryDigital Library
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  5. Kowalski, R. How to be Artificially Intelligent - the Logical Way. http://www-lp.doc.ic.ac.uk/UserPages/ staff/rak/, 2005.Google ScholarGoogle Scholar

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  1. Association search in semantic web: search + inference

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    • Published in

      cover image ACM Conferences
      WWW '05: Special interest tracks and posters of the 14th international conference on World Wide Web
      May 2005
      454 pages
      ISBN:1595930515
      DOI:10.1145/1062745

      Copyright © 2005 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 10 May 2005

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