Improving topic exploration in the blogosphere by detecting relevant segments
Renato Domínguez García; Alexandru Berlea; Philipp Scholl; Doreen Böhnstedt; Christoph Rensing ...
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. -- Blogs ; web page segmentation ; segment classification ; machine learning ; topic exploration
Year of publication: |
2009
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Authors: | Domínguez García, Renato ; Berlea, Alexandru ; Scholl, Philipp ; Böhnstedt, Doreen ; Rensing, Christoph |
Published in: |
Proceedings of I-KNOW '09 : 9th International Conference on Knowledge Management and Knowledge Technologies ; proceedings of I-SEMANTICS '09, 5th International Conference on Semantic Systems, Graz, Austria, September 2 - 4, 2009. - Graz : Verl. d. Techn. Univ. [u.a.], ISBN 978-3-85125-060-2. - 2009, p. 177-188
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Saved in:
freely available
Extent: | graph. Darst. |
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Type of publication: | Article |
Type of publication (narrower categories): | Aufsatz im Buch ; Book section |
Language: | English |
Notes: | Systemvoraussetzungen: Acrobat Reader |
Other identifiers: | hdl:10419/44444 [Handle] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10009508410
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