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Description
  • The paper describes a new method for association rule discovery in relational databases, which contain both quantitative and categorical attributes. Most of the methods developed in the past are based on initial equi-depth discretization of quantitative attributes. These approaches bring the loss of information. Distance-based methods are another kind of methods. They try to respect the semantics of data. The basic idea of the new method is to separate processing of categorical and quantitative attributes. The first step finds frequent itemsets containing only values of categorical attributes and then quantitative attributes are processed one by one. Discretization of values during quantitative attributes processing is distance-based. A new measure called average distance is introduced for these purposes. The paper describes the method and results of several experiments on real world data.
  • The paper describes a new method for association rule discovery in relational databases, which contain both quantitative and categorical attributes. Most of the methods developed in the past are based on initial equi-depth discretization of quantitative attributes. These approaches bring the loss of information. Distance-based methods are another kind of methods. They try to respect the semantics of data. The basic idea of the new method is to separate processing of categorical and quantitative attributes. The first step finds frequent itemsets containing only values of categorical attributes and then quantitative attributes are processed one by one. Discretization of values during quantitative attributes processing is distance-based. A new measure called average distance is introduced for these purposes. The paper describes the method and results of several experiments on real world data. (en)
Title
  • Mining Association Rules from Relational Data - Average Distance Based Method
  • Mining Association Rules from Relational Data - Average Distance Based Method (en)
skos:prefLabel
  • Mining Association Rules from Relational Data - Average Distance Based Method
  • Mining Association Rules from Relational Data - Average Distance Based Method (en)
skos:notation
  • RIV/00216305:26230/03:PU42633!RIV11-MSM-26230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • N, V
http://linked.open...iv/cisloPeriodika
  • 2888
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
  • 615619
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/03:PU42633
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • association rule, frequent itemset, categorical attribute, quantitative attribute (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV
  • [DB3829EE8D92]
http://linked.open...i/riv/nazevZdroje
  • Lecture Notes in Computer Science (IF 0,513)
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 2003
http://linked.open...iv/tvurceVysledku
  • Zendulka, Jaroslav
  • Bartík, Vladimír
issn
  • 0302-9743
number of pages
http://localhost/t...ganizacniJednotka
  • 26230
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