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  • In this paper, we propose a framework for association rules mining from data warehouses. This framework presents alliance between two business intelligence areas. First area is represented by data warehouse and data cube providing high quality data. The second area is represented by data mining, especially association rules mining providing an additional knowledge.<br>Association rules mining on data warehouses is different from mining on relational or transactional databases, because it deals with couple of dimensions, which form conceptual hierarchies. Thus we mine multi- and inter-dimensional association rules. There are several approaches how to mine such association rules described in literature. This framework presents a novel combination of the data cube processing - top-down (on product dimensions) and bottom-up (on domain dimensions). We presume division of dimensions on domain and product dimensions. <br>The framework works in the following steps.&nbsp; The first one represents obtaining fre
  • In this paper, we propose a framework for association rules mining from data warehouses. This framework presents alliance between two business intelligence areas. First area is represented by data warehouse and data cube providing high quality data. The second area is represented by data mining, especially association rules mining providing an additional knowledge.<br>Association rules mining on data warehouses is different from mining on relational or transactional databases, because it deals with couple of dimensions, which form conceptual hierarchies. Thus we mine multi- and inter-dimensional association rules. There are several approaches how to mine such association rules described in literature. This framework presents a novel combination of the data cube processing - top-down (on product dimensions) and bottom-up (on domain dimensions). We presume division of dimensions on domain and product dimensions. <br>The framework works in the following steps.&nbsp; The first one represents obtaining fre (en)
Title
  • Framework for mining of association rules from data warehouse
  • Framework for mining of association rules from data warehouse (en)
skos:prefLabel
  • Framework for mining of association rules from data warehouse
  • Framework for mining of association rules from data warehouse (en)
skos:notation
  • RIV/00216305:26230/08:PU80190!RIV10-MSM-26230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM0021630528)
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
  • 368497
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/08:PU80190
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • association rules, data warehouse, data mining (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [786810C1E6D3]
http://linked.open...v/mistoKonaniAkce
  • Hotel Hrebienok, Starý Smokovec
http://linked.open...i/riv/mistoVydani
  • Košice
http://linked.open...i/riv/nazevZdroje
  • ITAT 2008
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Chmelař, Petr
  • Stryka, Lukáš
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
  • Technická univerzita v Košiciach
https://schema.org/isbn
  • 978-80-969184-8-5
http://localhost/t...ganizacniJednotka
  • 26230
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