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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F06%3A00017162%21RIV10-MSM-14330___
rdf:type
n17:Vysledek skos:Concept
dcterms:description
The definite goal of this project is building tools for automatic filtering news reports on flood, for extracting information from such reports and the use of this extracted information for finding important terms (single words, name/verb phrases, named entities etc.) and eventually building a domain ontology. In this paper we focus on classifying sentences that describe either a situation or an action by means of machine learning. The results of various learning algorithms are discussed. We also bring first results on term extraction. The definite goal of this project is building tools for automatic filtering news reports on flood, for extracting information from such reports and the use of this extracted information for finding important terms (single words, name/verb phrases, named entities etc.) and eventually building a domain ontology. In this paper we focus on classifying sentences that describe either a situation or an action by means of machine learning. The results of various learning algorithms are discussed. We also bring first results on term extraction. The definite goal of this project is building tools for automatic filtering news reports on flood, for extracting information from such reports and the use of this extracted information for finding important terms (single words, name/verb phrases, named entities etc.) and eventually building a domain ontology. In this paper we focus on classifying sentences that describe either a situation or an action by means of machine learning. The results of various learning algorithms are discussed. We also bring first results on term extraction.
dcterms:title
Mining situations and actions from news Mining situations and actions from news Mining situations and actions from news
skos:prefLabel
Mining situations and actions from news Mining situations and actions from news Mining situations and actions from news
skos:notation
RIV/00216224:14330/06:00017162!RIV10-MSM-14330___
n3:aktivita
n16:Z
n3:aktivity
Z(MSM0021622418)
n3:dodaniDat
n5:2010
n3:domaciTvurceVysledku
n10:9343199 n10:5076382
n3:druhVysledku
n21:D
n3:duvernostUdaju
n15:S
n3:entitaPredkladatele
n18:predkladatel
n3:idSjednocenehoVysledku
485920
n3:idVysledku
RIV/00216224:14330/06:00017162
n3:jazykVysledku
n14:cze
n3:klicovaSlova
text filtering; information extraction; term extraction
n3:klicoveSlovo
n8:text%20filtering n8:term%20extraction n8:information%20extraction
n3:kontrolniKodProRIV
[3F4F3D9D0381]
n3:mistoKonaniAkce
Hradec Králové
n3:mistoVydani
Ostrava
n3:nazevZdroje
Znalosti 2006
n3:obor
n13:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:rokUplatneniVysledku
n5:2006
n3:tvurceVysledku
Popelínský, Lubomír Blaťák, Jan
n3:typAkce
n19:CST
n3:zahajeniAkce
2006-02-01+01:00
n3:zamer
n4:MSM0021622418
s:numberOfPages
9
n20:hasPublisher
Vysoká škola báňská - Technická univerzita Ostrava
n11:isbn
80-248-1001-8
n6:organizacniJednotka
14330