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Topic detection based on the PageRank's clustering property

dc.contributor.authorKubek, Mario
dc.contributor.authorUnger, Herwig
dc.contributor.editorEichler, Gerald
dc.contributor.editorKüpper, Axel
dc.contributor.editorSchau, Volkmar
dc.contributor.editorFouchal, Hacène
dc.contributor.editorUnger, Herwig
dc.contributor.editorEichler, Gerald
dc.contributor.editorKüpper, Axel
dc.contributor.editorSchau, Volkmar
dc.contributor.editorFouchal, Hacène
dc.contributor.editorUnger, Herwig
dc.date.accessioned2019-01-11T09:29:02Z
dc.date.available2019-01-11T09:29:02Z
dc.date.issued2011
dc.description.abstractThis 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.en
dc.identifier.isbn978-3-88579-280-2
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/18983
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof11th International Conference on Innovative Internet Community Systems (I2CS 2011)
dc.relation.ispartof11th International Conference on Innovative Internet Community Systems (I2CS 2011)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-186
dc.titleTopic detection based on the PageRank's clustering propertyen
dc.typeText/Conference Paper
gi.citation.endPage148
gi.citation.publisherPlaceBonn
gi.citation.startPage139
gi.conference.dateJune 15-17, 2011
gi.conference.locationBerlin
gi.conference.sessiontitleRegular Research Papers

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