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Statements

Subject Item
n2:RIV%2F61989592%3A15310%2F12%3A10225072%21RIV13-MSM-15310___
rdf:type
skos:Concept n12:Vysledek
dcterms:description
Fixpoints of Galois connections induced by object-attribute data tables represent important patterns that can be found in relational data. Such patterns are used in several data mining disciplines including formal concept analysis, frequent itemset and association rule mining, and Boolean factor analysis. In this paper we propose efficient algorithm for listing all fixpoints of Galois connections induced by object-attribute data. The algorithm, called FCbO, results as a modification of Kuznetsov's CbO in which we use more efficient canonicity test. We describe the algorithm, prove its correctness, discuss efficiency issues, and present an experimental evaluation of its performance and comparison with other algorithms. Fixpoints of Galois connections induced by object-attribute data tables represent important patterns that can be found in relational data. Such patterns are used in several data mining disciplines including formal concept analysis, frequent itemset and association rule mining, and Boolean factor analysis. In this paper we propose efficient algorithm for listing all fixpoints of Galois connections induced by object-attribute data. The algorithm, called FCbO, results as a modification of Kuznetsov's CbO in which we use more efficient canonicity test. We describe the algorithm, prove its correctness, discuss efficiency issues, and present an experimental evaluation of its performance and comparison with other algorithms.
dcterms:title
Fast Algorithm for Computing Fixpoints of Galois Connections Induced by Object-Attribute Relational Data Fast Algorithm for Computing Fixpoints of Galois Connections Induced by Object-Attribute Relational Data
skos:prefLabel
Fast Algorithm for Computing Fixpoints of Galois Connections Induced by Object-Attribute Relational Data Fast Algorithm for Computing Fixpoints of Galois Connections Induced by Object-Attribute Relational Data
skos:notation
RIV/61989592:15310/12:10225072!RIV13-MSM-15310___
n12:predkladatel
n13:orjk%3A15310
n3:aktivita
n7:P n7:Z
n3:aktivity
P(GAP103/10/1056), P(GPP202/10/P360), Z(MSM6198959214)
n3:cisloPeriodika
1
n3:dodaniDat
n16:2013
n3:domaciTvurceVysledku
n4:1236784 n4:1865994
n3:druhVysledku
n21:J
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n18:predkladatel
n3:idSjednocenehoVysledku
136195
n3:idVysledku
RIV/61989592:15310/12:10225072
n3:jazykVysledku
n11:eng
n3:klicovaSlova
frequent itemset mining; formal concept analysis; object-attribute data; Galois connection
n3:klicoveSlovo
n10:frequent%20itemset%20mining n10:Galois%20connection n10:object-attribute%20data n10:formal%20concept%20analysis
n3:kodStatuVydavatele
NL - Nizozemsko
n3:kontrolniKodProRIV
[524EC07BBB54]
n3:nazevZdroje
Information Sciences
n3:obor
n15:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n6:GAP103%2F10%2F1056 n6:GPP202%2F10%2FP360
n3:rokUplatneniVysledku
n16:2012
n3:svazekPeriodika
185
n3:tvurceVysledku
Vychodil, Vilém Outrata, Jan
n3:zamer
n14:MSM6198959214
s:issn
0020-0255
s:numberOfPages
14
n20:doi
10.1016/j.ins.2011.09.023
n9:organizacniJednotka
15310