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Statements

Subject Item
n2:RIV%2F61989100%3A27240%2F11%3A86080826%21RIV12-MPO-27240___
rdf:type
skos:Concept n13:Vysledek
dcterms:description
Fuzzy sets and fuzzy logic can be used for efficient data classification by fuzzy rules and fuzzy classifiers. This paper presents an application of genetic programming to the evolution of fuzzy classifiers based on extended Boolean queries. Extended Boolean queries are well known concept in the area of fuzzy information retrieval. An extended Boolean query represents a complex soft search expression that defines a fuzzy set on the collection of searched documents. We interpret the data mining task as a fuzzy information retrieval problem and we apply a proven method for query induction from data to find useful fuzzy classifiers. The ability of the genetic programming to evolve useful fuzzy classifiers is demonstrated on two use cases in which we detect faulty products in a product processing plant and discover intrusions in a computer network. Fuzzy sets and fuzzy logic can be used for efficient data classification by fuzzy rules and fuzzy classifiers. This paper presents an application of genetic programming to the evolution of fuzzy classifiers based on extended Boolean queries. Extended Boolean queries are well known concept in the area of fuzzy information retrieval. An extended Boolean query represents a complex soft search expression that defines a fuzzy set on the collection of searched documents. We interpret the data mining task as a fuzzy information retrieval problem and we apply a proven method for query induction from data to find useful fuzzy classifiers. The ability of the genetic programming to evolve useful fuzzy classifiers is demonstrated on two use cases in which we detect faulty products in a product processing plant and discover intrusions in a computer network.
dcterms:title
Fuzzy Classification by Evolutionary Algorithms Fuzzy Classification by Evolutionary Algorithms
skos:prefLabel
Fuzzy Classification by Evolutionary Algorithms Fuzzy Classification by Evolutionary Algorithms
skos:notation
RIV/61989100:27240/11:86080826!RIV12-MPO-27240___
n13:predkladatel
n22:orjk%3A27240
n5:aktivita
n14:P
n5:aktivity
P(FR-TI1/420)
n5:dodaniDat
n17:2012
n5:domaciTvurceVysledku
n16:9175970 Abraham Padath, Ajith n16:4347269 n16:6026877
n5:druhVysledku
n7:D
n5:duvernostUdaju
n18:S
n5:entitaPredkladatele
n20:predkladatel
n5:idSjednocenehoVysledku
200695
n5:idVysledku
RIV/61989100:27240/11:86080826
n5:jazykVysledku
n8:eng
n5:klicovaSlova
evolutionary computing; data mining; fuzzy sets
n5:klicoveSlovo
n19:data%20mining n19:evolutionary%20computing n19:fuzzy%20sets
n5:kontrolniKodProRIV
[AB6641AC49A2]
n5:mistoKonaniAkce
Anchorage
n5:mistoVydani
345 E 47TH ST, NEW YORK, NY 10017 USA
n5:nazevZdroje
2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
n5:obor
n21:IN
n5:pocetDomacichTvurcuVysledku
4
n5:pocetTvurcuVysledku
4
n5:projekt
n15:FR-TI1%2F420
n5:rokUplatneniVysledku
n17:2011
n5:tvurceVysledku
Platoš, Jan Abraham Padath, Ajith Krömer, Pavel Snášel, Václav
n5:typAkce
n6:WRD
n5:wos
000298615100053
n5:zahajeniAkce
2011-10-09+02:00
s:issn
1062-922X
s:numberOfPages
5
n11:doi
10.1109/ICSMC.2011.6083684
n4:hasPublisher
IEEE
n10:isbn
978-1-4577-0653-0
n23:organizacniJednotka
27240