Improving Topic Exploration in the Blogosphere by Detecting Relevant Segments
Key: DBS+09-1
Author: Renato Domínguez García, Alexandru Berlea, Philipp Scholl, Doreen Böhnstedt, Christoph Rensing, Ralf Steinmetz
Date: September 2009
Kind: In proceedings
Publisher: Verlag der Technischen Universität Graz
Book title: Proceedings of the I-Know 2009
Keywords: Blogs, web page segmentation, segment classification, machine learning, topic exploration
Abstract: With the accelerated growth of the blogosphere, automatically analyzing blogs (specifically extracting information) becomes increasingly important. Here, we focus on the fundamental task of automatically detecting blog topics in order to support users to explore a collection of blogs by focusing on different particular topics according to their interests. We show that topic exploration can be significantly improved (by up to 33\%) by using a novel approach to detecting blog page segments that contain relevant information for the blogs' topic.
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