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Frontiers of Structural and Civil Engineering

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    Heuristic solution using decision tree model for enhanced XML schema matching of bridge structural calculation documents

    . Department of Civil, Environmental and Architectural Engineering, University of Colorado at Boulder, Boulder, CO 80309, USA.. Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea

    Received：2020-10-20 Accepted： 2020-12-21 Available online：2020-12-21
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    10.1007/s11709-020-0666-8
    Cite this article
    Sang I. PARK, Sang-Ho LEE.Heuristic solution using decision tree model for enhanced XML schema matching of bridge structural calculation documents[J].Frontiers of Structural and Civil Engineering:0-

    Abstract

    Research on the quality of data in a structural calculation document (SCD) is lacking, although the SCD of a bridge is used as an essential reference during the entire lifecycle of the facility. XML Schema matching enables qualitative improvement of the stored data. This study aimed to enhance the applicability of XML Schema matching, which improves the speed and quality of information stored in bridge SCDs. First, the authors proposed a method of reducing the computing time for the schema matching of bridge SCDs. The computing speed of schema matching was increased by 13 to 1800 times by reducing the checking process of the correlations. Second, the authors developed a heuristic solution for selecting the optimal weight factors used in the matching process to maintain a high accuracy by introducing a decision tree. The decision tree model was built using the content elements stored in the SCD, design companies, bridge types, and weight factors as input variables, and the matching accuracy as the target variable. The inverse-calculation method was applied to extract the weight factors from the decision tree model for high-accuracy schema matching results.

    Keywords

    structural calculation document ; bridge structure ; XML Schema matching ; weight factor ; data mining ; decision tree model
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