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Clustering XML Documents for Web Based Learning

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Advances in Web-Based Learning – ICWL 2013 Workshops (ICWL 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8390))

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Abstract

The Web is increasingly used as a source of information for learning. Hence it is necessary that information on the web should be organized so that it can be used by the stakeholders efficiently. Most of the information in web is available in the form of XML documents. Grouping/clustering XML documents enhances the information retrieval process effectiveness. Computation of XML document similarity is a crucial task in clustering XML documents. In this paper we proposed a novel method to compute semantic structural similarity of an XML document by merging similar paths to address the above issues. In this method XML documents to be compared are represented by extracting all the paths from the root to the leaves and the comparison of paths is done based on a newly developed path matching algorithm. Similarity scores are given for exact, partial and contained in matches. In case of partial match merge operations are used namely the insertion of a new child (or descendants), parent (or ancestors) or both, and the creation of reference edges. More the number of merge operations more the dissimilarity of paths. Based on a similarity threshold the paths of XML documents are merged together and put in the same cluster and therefore avoiding pairwise similarity computations. Also, the matching process ensures the semantic structural similarity of the paths (i.e.) two XML paths may have a different order of hierarchy but semantically similar. Our proposed method shows an improved clustering accuracy.

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Author information

Authors and Affiliations

  1. PSG College of Technology, Coimbatore, India

    Ramanathan Periakaruppan & Rethinaswamy Nadarajan

Authors
  1. Ramanathan Periakaruppan
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  2. Rethinaswamy Nadarajan
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Corresponding author

Correspondence to Ramanathan Periakaruppan .

Editor information

Editors and Affiliations

  1. Dickson Computer Systems, Kowloon, Hong Kong SAR

    Dickson K. W. Chiu

  2. The University of Hong Kong, Pokfulam, Hong Kong SAR

    Minhong Wang

  3. University of Craiova, Craiova, Romania

    Elvira Popescu

  4. City University of Hong Kong, Hong Kong, Hong Kong SAR

    Qing Li

  5. City University of Hong Kong, Kowloon, Hong Kong SAR

    Rynson Lau

  6. Department of Computer Science and Information Engineering, National Central University, Jhongli City, Taiwan

    Timothy K. Shih

  7. Department of Electrical Engineering, National Cheng Kung University, Taiwan, Taiwan

    Chu-Sing Yang

  8. Digital Systems Centre for Research & Technology Hellas (CERTH), University of Piraeus Dept of Digital Systems, Piraeus, Greece

    Demetrios G. Sampson

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Periakaruppan, R., Nadarajan, R. (2015). Clustering XML Documents for Web Based Learning. In: Chiu, D., et al. Advances in Web-Based Learning – ICWL 2013 Workshops. ICWL 2013. Lecture Notes in Computer Science(), vol 8390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46315-4_24

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  • DOI: https://doi.org/10.1007/978-3-662-46315-4_24

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46314-7

  • Online ISBN: 978-3-662-46315-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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