General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Cecilia Xie
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • APC: 800 USD
    • E-mail: editor@ijcte.org
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IJCTE 2014 Vol.6(6): 472-475 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2014.V6.912

Data Mining in Semantic Web Data

K. Chomboon, N. Kaoungku, K. Kerdprasop, and N. Kerdprasop

Abstract—This research aims at studying the data mining role in semantic web data. Semantic web is popular in a variety of different applications, but research in data mining in semantic web data, appears less. As open source software for data mining in semantic web open source is minimal, and data model of the semantic web requires RDF or OWL format. These specific formats cannot be used directly in most data mining tools. We thus propose a methodology to mine data that appear in an RDF format. The mining process has been demonstrated through the use of R packages.

Index Terms—Data mining, semantic web, R language.

The authors are with the School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand (e-mail: chomboon.k@gmail.com).

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Cite:K. Chomboon, N. Kaoungku, K. Kerdprasop, and N. Kerdprasop, "Data Mining in Semantic Web Data," International Journal of Computer Theory and Engineering vol. 6, no. 6, pp. 472-475, 2014.


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