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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F05%3A00013632%21RIV10-MSM-14330___
rdf:type
skos:Concept n20:Vysledek
dcterms:description
The task of automated searching for interesting text documents frequently suffers from a~very poor balance among documents representing both positive and negative examples or from one completely missing class. This paper suggests the ranking approach based on the k-NN algorithm adapted for determining the similarity degree of new documents just to the representative positive collection. From the viewpoint of the precision-recall relation, a~user can decide in advance how many and how similar articles should be released through a filter. The task of automated searching for interesting text documents frequently suffers from a~very poor balance among documents representing both positive and negative examples or from one completely missing class. This paper suggests the ranking approach based on the k-NN algorithm adapted for determining the similarity degree of new documents just to the representative positive collection. From the viewpoint of the precision-recall relation, a~user can decide in advance how many and how similar articles should be released through a filter.
dcterms:title
Selecting Interesting Articles Using Their Similarity Based Only on Positive Examples Selecting Interesting Articles Using Their Similarity Based Only on Positive Examples
skos:prefLabel
Selecting Interesting Articles Using Their Similarity Based Only on Positive Examples Selecting Interesting Articles Using Their Similarity Based Only on Positive Examples
skos:notation
RIV/00216224:14330/05:00013632!RIV10-MSM-14330___
n3:aktivita
n11:Z
n3:aktivity
Z(MSM 143300003)
n3:dodaniDat
n14:2010
n3:domaciTvurceVysledku
n10:9299483 n10:1080644
n3:druhVysledku
n19:D
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n5:predkladatel
n3:idSjednocenehoVysledku
542155
n3:idVysledku
RIV/00216224:14330/05:00013632
n3:jazykVysledku
n18:eng
n3:klicovaSlova
machine learning; text categorization; text filtration; text similarity; k-NN; ranking
n3:klicoveSlovo
n9:text%20filtration n9:text%20categorization n9:text%20similarity n9:k-NN n9:ranking n9:machine%20learning
n3:kontrolniKodProRIV
[CCCA7F2641DB]
n3:mistoKonaniAkce
Mexico City, Mexico
n3:mistoVydani
Germany
n3:nazevZdroje
Computational linguistics and Intelligent Text Processing
n3:obor
n21:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:rokUplatneniVysledku
n14:2005
n3:tvurceVysledku
Žižka, Jan Hroza, Jiří
n3:typAkce
n17:WRD
n3:zahajeniAkce
2005-02-13+01:00
n3:zamer
n7:MSM%20143300003
s:numberOfPages
4
n4:hasPublisher
Springer-Verlag. (Berlin; Heidelberg)
n8:isbn
3-540-24523-5
n6:organizacniJednotka
14330