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Description
  • We focus on mining of first-order frequent patterns in temporal logic and introduce an extension of the downward refinement operator for this logic. We also discuss the needed modifications of a distributed ILP system when adressing temporal data.
  • We focus on mining of first-order frequent patterns in temporal logic and introduce an extension of the downward refinement operator for this logic. We also discuss the needed modifications of a distributed ILP system when adressing temporal data. (en)
Title
  • A Contribution to Learning in Temporal Logics
  • A Contribution to Learning in Temporal Logics (en)
skos:prefLabel
  • A Contribution to Learning in Temporal Logics
  • A Contribution to Learning in Temporal Logics (en)
skos:notation
  • RIV/00216224:14330/06:00017161!RIV10-MSM-14330___
http://linked.open...avai/riv/aktivita
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  • Z(MSM0021622418)
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  • 463473
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  • RIV/00216224:14330/06:00017161
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  • inductive logic programming; temporal data; refinement operator; parallel mining (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D4CDBE3FA5E9]
http://linked.open...v/mistoKonaniAkce
  • Santiago de Compostela, Spain
http://linked.open...i/riv/mistoVydani
  • Santiago de Compostela, Spain
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  • 16th International Conference on Inductive Logic Programming
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  • Popelínský, Lubomír
  • Blaťák, Jan
http://linked.open...vavai/riv/typAkce
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http://linked.open...n/vavai/riv/zamer
number of pages
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  • University of Coruna
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  • 84-9749-206-4
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  • 14330
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