An Analytic Aggregation-Based Ontology Alignment Approach with Multiple Matchers View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Fuqi Song , Gregory Zacharewicz , David Chen

ABSTRACT

A critical aspect of providing data interoperability relies on ontological alignment and the successful semantic integration. Ontology alignment is being applied to these domains as a fundamental component. Many basic matching techniques have been proposed, however in order to adapt to the diverse sources of ontology and enhance the matching ability, the crucial point facing is how to choose and combine different alignment algorithms. In this chapter, an approach with multiple alignment algorithms is described. The algorithms are proposed from lexical, semantic and structural levels of source ontology. The algorithms are chosen by a comprehensive pre-defined strategy, one or more specific algorithms will be chosen according to the features of entities to be matched. To aggregate the different matching results dynamically and automatically, Analytic Hierarchy Process (AHP) is applied innovatively based on three similarity indicators, which reflect the essential features of source ontology. The results of the benchmarking experiment suggested that the approach has strong matching ability. It obtained high precision and promising evaluation results. More... »

PAGES

143-159

References to SciGraph publications

  • 2005. CMC: Combining Multiple Schema-Matching Strategies Based on Credibility Prediction in DATABASE SYSTEMS FOR ADVANCED APPLICATIONS
  • 2004. QOM – Quick Ontology Mapping in THE SEMANTIC WEB – ISWC 2004
  • 2004. An API for Ontology Alignment in THE SEMANTIC WEB – ISWC 2004
  • 2013. Ontology Matching in NONE
  • 2005. A String Metric for Ontology Alignment in THE SEMANTIC WEB – ISWC 2005
  • Book

    TITLE

    Advanced Techniques for Knowledge Engineering and Innovative Applications

    ISBN

    978-3-642-42016-0
    978-3-642-42017-7

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-42017-7_11

    DOI

    http://dx.doi.org/10.1007/978-3-642-42017-7_11

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1040771086


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