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MAPSOM: User Involvement in Ontology Matching

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Semantic Technology (JIST 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8388))

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Abstract

This paper presents a semi-automatic similarity aggregating system for ontology matching problem. The system consists of two main parts. The first part is aggregation of similarity measures with the help of self-organizing map. The second part incorporates user feedback for refining self-organizing map outcomes. The system calculates different similarity measures (e.g., string-based similarity measure, WordNet-based similarity measure...) to cover different causes of semantic heterogeneity. The next step is similarity aggregation by means of the self-organizing map and the ward clustering. The final step is the active learning phase for results tuning. We implemented this idea as MAPSOM framework. Our experimental results show that MAPSOM framework can be used for problems where the highest precision is needed.

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Notes

  1. 1.

    http://oaei.ontologymatching.org/2013/benchmarks/

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Acknowledgements

This research has been supported by the Grant Agency of the Czech Technical University in Prague, grant No. SGS12/188/OHK3/3T/13.

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Authors and Affiliations

  1. Czech Technical University in Prague, Zikova 1903/4, Prague, Czech Republic

    Václav Jirkovský

  2. Rockwell Automation Research and Development Center, Pekařská 695/10a, Prague, Czech Republic

    Václav Jirkovský

  3. National Institute of Informatics, Tokyo, 101-8430, Japan

    Ryutaro Ichise

Authors
  1. Václav Jirkovský
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  2. Ryutaro Ichise
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Correspondence to Václav Jirkovský .

Editor information

Editors and Affiliations

  1. Yonsei University, Seoul, Korea, Republic of (South Korea)

    Wooju Kim

  2. Indiana University, Bloomington, Indiana, USA

    Ying Ding

  3. Seoul National University, Seoul, Korea, Republic of (South Korea)

    Hong-Gee Kim

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Jirkovský, V., Ichise, R. (2014). MAPSOM: User Involvement in Ontology Matching. In: Kim, W., Ding, Y., Kim, HG. (eds) Semantic Technology. JIST 2013. Lecture Notes in Computer Science(), vol 8388. Springer, Cham. https://doi.org/10.1007/978-3-319-06826-8_26

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  • DOI: https://doi.org/10.1007/978-3-319-06826-8_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06825-1

  • Online ISBN: 978-3-319-06826-8

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