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Type of publication: Article in peer-reviewed Lithuanian conference proceedings (P1f);Straipsnis recenzuojamoje Lietuvos konferencijos medžiagoje (P1f)
Field of Science: Computer science (N009);Informatika (N009)
Author(s): Krilavičius, Tomas;Mackutė-Varoneckienė, Aušra;Ciganaitė, Greta
Title: Text documents clustering
Is part of: Informacinės technologijos : 19-oji tarpuniversitetinė tarptautinė magistrantų ir doktorantų konferencija "Informacinė visuomenė ir universitetinės studijos" (IVUS 2014) : konferencijos pranešimų medžiaga. Kaunas : Technologija, 19 (2014)
Extent: p. 90-93
Date: 2014
Keywords: Similarity measures;Klasterizavimas;Text document clustering
Abstract: Big amounts of textual information are generated every day, and existing techniques can hardly deal with such information flow. However, users expect fast and exact information management and retrieval tools. Clustering is a well known technique for grouping similar data and in such a way making it more manageable and usable. Text clustering is an adaptation of clustering for a very specific data - documents. However, it is not transferable directly to any language, i.e. specifics of language influence performance quite a lot, as shows results for English and other well investigated languages. In this paper we apply different distances and clustering approaches for Lithuanian data, discuss results and provide recommendations for documents in Lithuanian clustering
Affiliation(s): Taikomosios informatikos katedra
Informatikos fakultetas
Baltijos pažangių technologijų institutas, Vilnius
Vytauto Didžiojo universitetas
Appears in Collections:3. Konferencijų medžiaga / Conference materials
Universiteto mokslo publikacijos / University Research Publications

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