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Description
  • Classically, unsupervised machine learning techniques are applied on data sets with fixednumber of attributes (variables). However, many problems encountered in the field of infor-metrics face us with the need to extend these kinds of methods in a way such that they maybe computed over a set of nonincreasingly ordered vectors of unequal lengths. Thus, in this paper, some new dissimilarity measures (metrics) are introduced and studied. Owing tothat we may use, e.g. hierarchical clustering algorithms in order to determine an input dataset?s partition consisting of sets of producers that are homogeneous not only with respect to the quality of information resources, but also their quantity.
  • Classically, unsupervised machine learning techniques are applied on data sets with fixednumber of attributes (variables). However, many problems encountered in the field of infor-metrics face us with the need to extend these kinds of methods in a way such that they maybe computed over a set of nonincreasingly ordered vectors of unequal lengths. Thus, in this paper, some new dissimilarity measures (metrics) are introduced and studied. Owing tothat we may use, e.g. hierarchical clustering algorithms in order to determine an input dataset?s partition consisting of sets of producers that are homogeneous not only with respect to the quality of information resources, but also their quantity. (en)
Title
  • Problems and challenges of information resourcesproducers? clustering
  • Problems and challenges of information resourcesproducers? clustering (en)
skos:prefLabel
  • Problems and challenges of information resourcesproducers? clustering
  • Problems and challenges of information resourcesproducers? clustering (en)
skos:notation
  • RIV/61988987:17610/15:A1501DLG!RIV15-MSM-17610___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0070)
http://linked.open...iv/cisloPeriodika
  • 1
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
  • 364
http://linked.open...ai/riv/idVysledku
  • RIV/61988987:17610/15:A1501DLG
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Aggregation; Hierarchical clustering; Distance; Metric (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • NL - Nizozemsko
http://linked.open...ontrolniKodProRIV
  • [DF06CE8D7EB2]
http://linked.open...i/riv/nazevZdroje
  • J INFORMETR
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 9
http://linked.open...iv/tvurceVysledku
  • Mesiar, Radko
  • Gagolewski, Marek
  • Cena, Anna
issn
  • 1751-1577
number of pages
http://localhost/t...ganizacniJednotka
  • 17610
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