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Statements

Subject Item
n2:RIV%2F61989592%3A15310%2F11%3A10225088%21RIV12-GA0-15310___
rdf:type
skos:Concept n14:Vysledek
dcterms:description
The paper presents a new approach to factor analysis of three-way ordinal data, i.e. data described by a 3-dimensional matrix I with values in an ordered scale. The matrix describes a relationship between objects, attributes, and conditions. The problem consists in find- ing factors for I, i.e. finding a decomposition of I into three matrices, an object-factor matrix A, an attribute-factor matrix B, and a condition- factor matrix C, with the number of factors as small as possible. The difference from the decomposition-based methods of analysis of three- way data consists in the composition operator and the constraint on A, B, and C to be matrices with values in an ordered scale. We prove that optimal decompositions are achieved by using triadic concepts of I, developed within formal concept analysis, and provide results on natu- ral transformations between the space of attributes and conditions and the space of factors. The paper presents a new approach to factor analysis of three-way ordinal data, i.e. data described by a 3-dimensional matrix I with values in an ordered scale. The matrix describes a relationship between objects, attributes, and conditions. The problem consists in find- ing factors for I, i.e. finding a decomposition of I into three matrices, an object-factor matrix A, an attribute-factor matrix B, and a condition- factor matrix C, with the number of factors as small as possible. The difference from the decomposition-based methods of analysis of three- way data consists in the composition operator and the constraint on A, B, and C to be matrices with values in an ordered scale. We prove that optimal decompositions are achieved by using triadic concepts of I, developed within formal concept analysis, and provide results on natu- ral transformations between the space of attributes and conditions and the space of factors.
dcterms:title
Factorizing three-way ordinal data using triadic formal concepts Factorizing three-way ordinal data using triadic formal concepts
skos:prefLabel
Factorizing three-way ordinal data using triadic formal concepts Factorizing three-way ordinal data using triadic formal concepts
skos:notation
RIV/61989592:15310/11:10225088!RIV12-GA0-15310___
n14:predkladatel
n15:orjk%3A15310
n4:aktivita
n13:P
n4:aktivity
P(GAP202/10/0262)
n4:cisloPeriodika
-
n4:dodaniDat
n5:2012
n4:domaciTvurceVysledku
n16:9482547 n16:9623264 n16:1236784
n4:druhVysledku
n8:J
n4:duvernostUdaju
n6:S
n4:entitaPredkladatele
n17:predkladatel
n4:idSjednocenehoVysledku
199188
n4:idVysledku
RIV/61989592:15310/11:10225088
n4:jazykVysledku
n18:eng
n4:klicovaSlova
concept analysis, matrix decomposition, tree-way data
n4:klicoveSlovo
n7:matrix%20decomposition n7:concept%20analysis n7:tree-way%20data
n4:kodStatuVydavatele
DE - Spolková republika Německo
n4:kontrolniKodProRIV
[DEFE09CF539E]
n4:nazevZdroje
Lecture Notes in Artificial Intelligence
n4:obor
n12:IN
n4:pocetDomacichTvurcuVysledku
3
n4:pocetTvurcuVysledku
3
n4:projekt
n9:GAP202%2F10%2F0262
n4:rokUplatneniVysledku
n5:2011
n4:svazekPeriodika
7022
n4:tvurceVysledku
Vychodil, Vilém Bělohlávek, Radim Osička, Petr
s:issn
0302-9743
s:numberOfPages
12
n19:organizacniJednotka
15310