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  • The aim of this short paper is to present a general method of using background knowledge to impose constraints in conceptual clustering of object-attribute relational data. The proposed method uses the background knowledge to extract only particular clusters from the input data -- those which are compatible with the background knowledge and thus satisfy the constraint. As a result, the method allows for extracting less clusters in a shorter time which are in addition more interesting. The paper presents the idea of constraints formalized by means of closure operators and introduces such constraints to formal concept analysis. Among the bene ts of the presented approach are its versatility (the approach covers several examples studied before, e.g. extraction of closed frequent itemsets in generation of non-redundant association rules) and computational efficiency. Due to scope limitations, we present the main ideas only. Details will be available in a full version of this paper.
  • The aim of this short paper is to present a general method of using background knowledge to impose constraints in conceptual clustering of object-attribute relational data. The proposed method uses the background knowledge to extract only particular clusters from the input data -- those which are compatible with the background knowledge and thus satisfy the constraint. As a result, the method allows for extracting less clusters in a shorter time which are in addition more interesting. The paper presents the idea of constraints formalized by means of closure operators and introduces such constraints to formal concept analysis. Among the bene ts of the presented approach are its versatility (the approach covers several examples studied before, e.g. extraction of closed frequent itemsets in generation of non-redundant association rules) and computational efficiency. Due to scope limitations, we present the main ideas only. Details will be available in a full version of this paper. (en)
Title
  • Background Knowledge in Formal Concept Analysis: Constraints via Closure Operators.
  • Background Knowledge in Formal Concept Analysis: Constraints via Closure Operators. (en)
skos:prefLabel
  • Background Knowledge in Formal Concept Analysis: Constraints via Closure Operators.
  • Background Knowledge in Formal Concept Analysis: Constraints via Closure Operators. (en)
skos:notation
  • RIV/61989592:15310/10:10216466!RIV11-MSM-15310___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6198959214)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 248339
http://linked.open...ai/riv/idVysledku
  • RIV/61989592:15310/10:10216466
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • formal concept analysis, background knowledge, closure operator (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [35F81F76436A]
http://linked.open...v/mistoKonaniAkce
  • Sierre, Švýcarsko
http://linked.open...i/riv/mistoVydani
  • New York
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 25th Symposium On Applied Computing
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Bělohlávek, Radim
  • Vychodil, Vilém
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • ACM Press
https://schema.org/isbn
  • 978-1-60558-638-0
http://localhost/t...ganizacniJednotka
  • 15310
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