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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F11%3A00185744%21RIV12-MSM-21230___
rdf:type
n8:Vysledek skos:Concept
rdfs:seeAlso
http://www.springerlink.com/content/w450n21140245x78/
dcterms:description
We describe a new approach to the application of stochastic search in Inductive Logic Programming (ILP). Contrary to traditional approaches we do not focus directly on evolving logical concepts. Instead, our refinement-based approach uses the stochastic optimization process to iteratively adapt the initial working concept. It enables using available background knowledge both for efficiently restricting the search space and for directing the search. Thereby, the search is more flexible, less problem-specific and the framework can be easily used with any stochastic search algorithm within ILP domain. Experimental results on several data sets verify the usefulness of this approach. We describe a new approach to the application of stochastic search in Inductive Logic Programming (ILP). Contrary to traditional approaches we do not focus directly on evolving logical concepts. Instead, our refinement-based approach uses the stochastic optimization process to iteratively adapt the initial working concept. It enables using available background knowledge both for efficiently restricting the search space and for directing the search. Thereby, the search is more flexible, less problem-specific and the framework can be easily used with any stochastic search algorithm within ILP domain. Experimental results on several data sets verify the usefulness of this approach.
dcterms:title
Context-Sensitive Refinements for Stochastic Optimisation Algorithms in Inductive Logic Programming Context-Sensitive Refinements for Stochastic Optimisation Algorithms in Inductive Logic Programming
skos:prefLabel
Context-Sensitive Refinements for Stochastic Optimisation Algorithms in Inductive Logic Programming Context-Sensitive Refinements for Stochastic Optimisation Algorithms in Inductive Logic Programming
skos:notation
RIV/68407700:21230/11:00185744!RIV12-MSM-21230___
n8:predkladatel
n17:orjk%3A21230
n3:aktivita
n21:Z n21:P
n3:aktivity
P(GAP103/10/1875), Z(MSM6840770012)
n3:cisloPeriodika
1
n3:dodaniDat
n15:2012
n3:domaciTvurceVysledku
n12:1775022 n12:5775590
n3:druhVysledku
n7:J
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n4:predkladatel
n3:idSjednocenehoVysledku
191818
n3:idVysledku
RIV/68407700:21230/11:00185744
n3:jazykVysledku
n6:eng
n3:klicovaSlova
Evolutionary Algorithms; First Order Logic; Inductive Logic Programming; Relational Learning; Stochastic Search
n3:klicoveSlovo
n13:Evolutionary%20Algorithms n13:Stochastic%20Search n13:Inductive%20Logic%20Programming n13:Relational%20Learning n13:First%20Order%20Logic
n3:kodStatuVydavatele
NL - Nizozemsko
n3:kontrolniKodProRIV
[6F1D1CD1A7A4]
n3:nazevZdroje
Artificial Intelligence Review
n3:obor
n16:JC
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n20:GAP103%2F10%2F1875
n3:rokUplatneniVysledku
n15:2011
n3:svazekPeriodika
35
n3:tvurceVysledku
Buryan, Petr Kubalík, Jiří
n3:wos
000286054000002
n3:zamer
n14:MSM6840770012
s:issn
0269-2821
s:numberOfPages
18
n10:doi
10.1007/s10462-010-9181-y
n11:organizacniJednotka
21230