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  • Minimizing Human Effort in Reconciling Match Networks

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    NguyenPUB2380.pdf (315.8Kb)
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    Accepted Manuscript (AM)
    Author(s)
    Hung, Quoc Viet Nguyen
    Wijaya, Tri Kurniawan
    Miklos, Zoltan
    Aberer, Karl
    Levy, Eliezer
    Shafran, Victor
    Gal, Avigdor
    Weidlich, Matthias
    Griffith University Author(s)
    Nguyen, Henry
    Year published
    2013
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    Abstract
    Schema and ontology matching is a process of establishing correspondences between schema attributes and ontology concepts, for the purpose of data integration. Various commercial and academic tools have been developed to support this task. These tools provide impressive results on some datasets. However, as the matching is inherently uncertain, the developed heuristic techniques give rise to results that are not completely correct. In practice, post-matching human expert effort is needed to obtain a correct set of correspondences. We study this post-matching phase with the goal of reducing the costly human effort. We formally ...
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    Schema and ontology matching is a process of establishing correspondences between schema attributes and ontology concepts, for the purpose of data integration. Various commercial and academic tools have been developed to support this task. These tools provide impressive results on some datasets. However, as the matching is inherently uncertain, the developed heuristic techniques give rise to results that are not completely correct. In practice, post-matching human expert effort is needed to obtain a correct set of correspondences. We study this post-matching phase with the goal of reducing the costly human effort. We formally model this human-assisted phase and introduce a process of matching reconciliation that incrementally leads to identifying the correct correspondences. We achieve the goal of reducing the involved human effort by exploiting a network of schemas that are matched against each other.We express the fundamental matching constraints present in the network in a declarative formalism, Answer Set Programming that in turn enables to reason about necessary user input. We demonstrate empirically that our reasoning and heuristic techniques can indeed substantially reduce the necessary human involvement.
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    Journal Title
    Lecture Notes in Computer Science
    Volume
    8217
    DOI
    https://doi.org/10.1007/978-3-642-41924-9_19
    Copyright Statement
    © 2013 Springer International Publishing AG. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com.
    Subject
    Database systems
    Publication URI
    http://hdl.handle.net/10072/348260
    Collection
    • Journal articles

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