Keyword extraction for text characterization

dc.contributor.author	Renz, Ingrid
dc.contributor.author	Ficzay, Andrea
dc.contributor.author	Hitzler, Holger
dc.contributor.editor	Düsterhöft, Antje
dc.contributor.editor	Thalheim, Bernhard
dc.date.accessioned	2019-11-14T11:21:42Z
dc.date.available	2019-11-14T11:21:42Z
dc.date.issued	2003
dc.description.abstract	Keywords are valuable means for characterizing texts. In order to extract keywords we propose an efficient and robust, languageand domainindependent approach which is based on small word parts (quadgrams). The basic algorithm can be improved by re-examining and re-ranking keywords using edit distance (i.e. Levenshtein distance) and an algorithm based on the relativistic addition of velocities (here: weights). For the purpose of evaluation, we compare our approach to frequency-based keyword extraction (exemplary text collection: 45000 intranet documents in German and English).	en
dc.identifier.isbn	3-88579-358-X
dc.identifier.pissn	1617-5468
dc.identifier.uri	https://dl.gi.de/handle/20.500.12116/29889
dc.language.iso	en
dc.publisher	Gesellschaft für Informatik e.V.
dc.relation.ispartof	Natural language processing and information systems
dc.relation.ispartofseries	Lecture Notes in Informatics (LNI) - Proceedings, Volume P-29
dc.title	Keyword extraction for text characterization	en
dc.type	Text/Conference Paper
gi.citation.endPage	234
gi.citation.publisherPlace	Bonn
gi.citation.startPage	228
gi.conference.date	June 2003
gi.conference.location	Burg (Spreewald)
gi.conference.sessiontitle	Regular Research Papers

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