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Combining Uncertain Outputs from Multiple Ontology Matchers

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Scalable Uncertainty Management (SUM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4772))

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Abstract

An ontology matching method (or a matcher) aims at matching every entity (or concept) in one ontology to the most suitable entity (or entities) in another ontology. Usually it is almost impossible to find a perfect match in the second ontology for every entity in the first ontology, so a matcher generally returns a set of possible matches with some weights (uncertainty) attached to each pair of match. In order to improve a matching result, several matchers can be used and the matched results from these matchers are combined with suitable approaches. In this paper, we first propose two new matchers among three matchers we use. We then address the need of dealing with uncertainties in mapping by investigating how some uncertainty reasoning frameworks can be used to combine matching results. We apply both the Dempster Shafer theory of evidence (DS theory) and Possibility Theory to merge the results computed by different matchers. Our experimental results and comparisons with related work indicate that integrating these theories to deal with uncertain ontology matching is a promising way to improve the overall matching results.

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Authors and Affiliations

  1. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, BT7 1NN, UK

    Ying Wang, Weiru Liu & David Bell

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  1. Ying Wang
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  2. Weiru Liu
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  3. David Bell
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Henri Prade V. S. Subrahmanian

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Wang, Y., Liu, W., Bell, D. (2007). Combining Uncertain Outputs from Multiple Ontology Matchers. In: Prade, H., Subrahmanian, V.S. (eds) Scalable Uncertainty Management. SUM 2007. Lecture Notes in Computer Science(), vol 4772. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75410-7_15

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  • DOI: https://doi.org/10.1007/978-3-540-75410-7_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75407-7

  • Online ISBN: 978-3-540-75410-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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