About: Using Semi-discrete Decomposition for Topic Identification

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	In the area of information retrieval, the dimension of document vectors plays an important role. We may need to find a few words or concepts, which characterize the document based on its contents, to overcome the problem of the %22curse of dimensionality%22, which makes indexing of high-dimensional data problematic. To do so, we earlier proposed a Wordnet and Wordnet+SVD (Singular value decomposition) based model for dimension reduction. While LSI concepts contain identifiable terms in top-level concepts, we show in this paper that semi-discrete decomposition provides mostly smaller list of terms and we need to cope only with ternary weights. With this size of term list, the identification of document's topic becomes much more feasible. In the area of information retrieval, the dimension of document vectors plays an important role. We may need to find a few words or concepts, which characterize the document based on its contents, to overcome the problem of the %22curse of dimensionality%22, which makes indexing of high-dimensional data problematic. To do so, we earlier proposed a Wordnet and Wordnet+SVD (Singular value decomposition) based model for dimension reduction. While LSI concepts contain identifiable terms in top-level concepts, we show in this paper that semi-discrete decomposition provides mostly smaller list of terms and we need to cope only with ternary weights. With this size of term list, the identification of document's topic becomes much more feasible. (en)
Title	Using Semi-discrete Decomposition for Topic Identification Using Semi-discrete Decomposition for Topic Identification (en)
skos:prefLabel	Using Semi-discrete Decomposition for Topic Identification Using Semi-discrete Decomposition for Topic Identification (en)
skos:notation	RIV/61989100:27240/08:00021058!RIV11-GA0-27240___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GA201/06/0756)
http://linked.open...vai/riv/dodaniDat	2011
http://linked.open...aciTvurceVysledku	Pokorný, Jan Snášel, Václav Moravec, Pavel
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola báňská - Technická univerzita Ostrava / Fakulta elektrotechniky a informatiky
http://linked.open...dnocenehoVysledku	401890
http://linked.open...ai/riv/idVysledku	RIV/61989100:27240/08:00021058
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	WordNet, LSI, Ontology, SDD (en)
http://linked.open.../riv/klicoveSlovo	LSI Ontology WordNet SDD
http://linked.open...ontrolniKodProRIV	[7B73C4255328]
http://linked.open...v/mistoKonaniAkce	KAOHSIUNG, Taiwan
http://linked.open...i/riv/mistoVydani	Los Alamitos, California
http://linked.open...i/riv/nazevZdroje	ISDA 2008: EIGHTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 2, PROCEEDINGS
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Development of a native storage for XML data
http://linked.open...UplatneniVysledku	2008
http://linked.open...iv/tvurceVysledku	Moravec, Pavel Pokorný, Jan Snášel, Václav
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open...ain/vavai/riv/wos	000262692600076
http://linked.open.../riv/zahajeniAkce	2008-11-26 (xsd:date)
number of pages	6 (xsd:int)
http://purl.org/ne...btex#hasPublisher	IEEE Computer Society
https://schema.org/isbn	978-0-7695-3382-7
http://localhost/t...ganizacniJednotka	27240

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