Topic detection based on the PageRank's clustering property

Zusammenfassung
This paper introduces a method to cluster graphs of semantically related terms from texts using PageRank calculations for use in the field of text mining, e.g. to automatically discover different topics in a text corpus. It is evaluated by providing empirical results of tests by applying this method on real text corpora. It is shown that this application of the PageRank formula realizes suitable clustering such that the mean similarity between the terms in the clusters reaches a high level. A special state transition in the mean term similarity is discussed when analysing texts with stopwords.
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  • BibTeX
Kubek, M. & Unger, H., (2011). Topic detection based on the PageRank's clustering property. In: Eichler, G., Küpper, A., Schau, V., Fouchal, H., Unger, H., Eichler, G., Küpper, A., Schau, V., Fouchal, H. & Unger, H. (Hrsg.), 11th International Conference on Innovative Internet Community Systems (I2CS 2011). Bonn: Gesellschaft für Informatik e.V.. (S. 139-148).
@inproceedings{mci/Kubek2011,
author = {Kubek, Mario AND Unger, Herwig},
title = {Topic detection based on the PageRank's clustering property},
booktitle = {11th International Conference on Innovative Internet Community Systems (I2CS 2011)},
year = {2011},
editor = {Eichler, Gerald AND Küpper, Axel AND Schau, Volkmar AND Fouchal, Hacène AND Unger, Herwig AND Eichler, Gerald AND Küpper, Axel AND Schau, Volkmar AND Fouchal, Hacène AND Unger, Herwig} ,
pages = { 139-148 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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Mehr Information

ISBN: 978-3-88579-280-2
ISSN: 1617-5468
Datum: 2011
Sprache: en (en)
Typ: Text/Conference Paper
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