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International Conference on Hybrid Artificial Intelligence Systems

HAIS 2016: Hybrid Artificial Intelligent Systems pp 14–26Cite as

SemSynX: Flexible Similarity Analysis of XML Data via Semantic and Syntactic Heterogeneity/Homogeneity Detection

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9648))

Abstract

In this paper we introduce and experimentally assess SemSynX, a novel technique for supporting similarity analysis of XML data via semantic and syntactic heterogeneity/homogeneity detection. Given two XML trees, SemSynX retrieves a list of semantic and syntactic heterogeneity/homogeneity matches of objects (i.e., elements, values, tags, attributes) occurring in certain paths of the trees. A local score that takes into account the path and value similarity is given for each heterogeneity/homogeneity found. A global score that summarizes the number of equal matches as well as the local scores globally is also provided. The proposed technique is highly customizable, and it permits the specification of thresholds for the requested degree of similarity for paths and values as well as for the degree of relevance for path and value matching. It thus makes possible to “adjust” the similarity analysis depending on the nature of the input XML trees. SemSynX has been implemented in terms of a XQuery library, as to enhance interoperability with other XML processing tools. To complete our analytical contributions, a comprehensive experimental assessment and evaluation of SemSynX over several classes of XML documents is provided.

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Notes

  1. 1.

    The use of keys is not mandatory in our approach, but keys are used in the running example to guide similarity search.

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Acknowledgments

This work was funded by the EU ERDF and the Spanish Ministry of Economy and Competitiveness (MINECO) under Project TIN2013-44742-C4-4-R as well as by the Andalusian Regional Government under Project P10-TIC-6114.

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Authors and Affiliations

  1. Informatics Department, University of Almería, Almería, Spain

    Jesús M. Almendros-Jiménez

  2. DIA Department, University of Trieste and ICAR-CNR, Trieste, Italy

    Alfredo Cuzzocrea

Authors
  1. Jesús M. Almendros-Jiménez
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  2. Alfredo Cuzzocrea
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Correspondence to Jesús M. Almendros-Jiménez .

Editor information

Editors and Affiliations

  1. Universidad Pablo de Olavide, Sevilla, Spain

    Francisco Martínez-Álvarez

  2. Universidad Pablo de Olavide, Sevilla, Spain

    Alicia Troncoso

  3. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Almendros-Jiménez, J.M., Cuzzocrea, A. (2016). SemSynX: Flexible Similarity Analysis of XML Data via Semantic and Syntactic Heterogeneity/Homogeneity Detection. In: Martínez-Álvarez, F., Troncoso, A., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2016. Lecture Notes in Computer Science(), vol 9648. Springer, Cham. https://doi.org/10.1007/978-3-319-32034-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-32034-2_2

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  • Online ISBN: 978-3-319-32034-2

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