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XML Mining for Semantic Web

XML Mining for Semantic Web

Rafael Berlanga, Victoria Nebot
Copyright: © 2013 |Pages: 25
ISBN13: 9781466624559|ISBN10: 1466624558|EISBN13: 9781466624566
DOI: 10.4018/978-1-4666-2455-9.ch031
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MLA

Berlanga, Rafael, and Victoria Nebot. "XML Mining for Semantic Web." Data Mining: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2013, pp. 625-649. https://doi.org/10.4018/978-1-4666-2455-9.ch031

APA

Berlanga, R. & Nebot, V. (2013). XML Mining for Semantic Web. In I. Management Association (Ed.), Data Mining: Concepts, Methodologies, Tools, and Applications (pp. 625-649). IGI Global. https://doi.org/10.4018/978-1-4666-2455-9.ch031

Chicago

Berlanga, Rafael, and Victoria Nebot. "XML Mining for Semantic Web." In Data Mining: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 625-649. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2455-9.ch031

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Abstract

This chapter describes the convergence of two influential technologies in the last decade, namely data mining (DM) and the Semantic Web (SW). The wide acceptance of new SW formats for describing semantics-aware and semistructured contents have spurred on the massive generation of semantic annotations and large-scale domain ontologies for conceptualizing their concepts. As a result, a huge amount of both knowledge and semantic-annotated data is available in the web. DM methods have been very successful in discovering interesting patterns which are hidden in very large amounts of data. However, DM methods have been largely based on simple and flat data formats which are far from those available in the SW. This chapter reviews and discusses the main DM approaches proposed so far to mine SW data as well as those that have taken into account the SW resources and tools to define semantics-aware methods.

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