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A Study on Automatically Extracted Keywords in Text Categorization
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. Datorlingvistik.ORCID iD: 0000-0002-4838-6518
2006 (English)In: Proceedings of International Conference of Association for Computational Linguistics, 2006Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a study on if and how automatically extracted

keywords can be used to improve text categorization. In summary we

show that a higher performance --- as measured by micro-averaged

F-measure on a standard text categorization collection --- is achieved

when the full-text representation is combined with the automatically

extracted keywords. The combination is obtained by giving higher

weights to words in the full-texts that are also extracted as

keywords. We also present results for experiments in which the

keywords are the only input to the categorizer, either represented as

unigrams or intact. Of these two experiments, the unigrams have the

best performance, although neither performs as well as headlines only.

Place, publisher, year, edition, pages
2006.
National Category
Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:uu:diva-18164OAI: oai:DiVA.org:uu-18164DiVA: diva2:45936
Conference
International Conference of Association for Computational Linguistics
Available from: 2006-11-20 Created: 2006-11-20 Last updated: 2017-01-25

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Megyesi, Beata

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