Process Model for Content Extraction from Weblogs

Andreas Schieber and Andreas Hilbert
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Andreas Schieber: University of Technology Dresden, Dresden, Germany
Andreas Hilbert: University of Technology Dresden, Dresden, Germany

International Journal of Intelligent Information Technologies (IJIIT), 2014, vol. 10, issue 2, 20-36

Abstract: This paper develops and evaluates a BPMN-based process model which identifies and extracts blog content from the web and stores its textual data in a data warehouse for further analyses. Depending on the characteristics of the technologies used to create the weblogs, the process has to perform specific tasks in order to extract blog content correctly. The paper describes three phases: extraction, transformation and loading of data in a repository specifically adapted for blog content extraction. It highlights the objectives in these phases which must be achieved to ensure the correct extraction. The authors integrate the described process in a previously developed framework for blog mining. The authors' process model closes the conceptual gap in this framework as well as the gap in current research of blog mining process models. Furthermore, it can easily be adapted for other web extraction proposals.

Date: 2014
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