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Description
  • In this work we have studied, evaluated and proposed different swarm intelligence techniques for mining information from loosely structured medical textual records with no a priori knowledge (a large dataset). The output of this task is a set of ordered/nominal attributes suitable for rule discovery mining. First, classical approaches such as basic statistic approaches, single and multiple word frequency analysis, etc., have been used to simplify the textual data and provide an overview of the data. Finally, an ant-inspired self-learning approach has been used to automatically provide a simplified dominant structure, presenting structure of the records in the human readable form that can be further utilized in the mining process as it describes the vast majority of the records.
  • In this work we have studied, evaluated and proposed different swarm intelligence techniques for mining information from loosely structured medical textual records with no a priori knowledge (a large dataset). The output of this task is a set of ordered/nominal attributes suitable for rule discovery mining. First, classical approaches such as basic statistic approaches, single and multiple word frequency analysis, etc., have been used to simplify the textual data and provide an overview of the data. Finally, an ant-inspired self-learning approach has been used to automatically provide a simplified dominant structure, presenting structure of the records in the human readable form that can be further utilized in the mining process as it describes the vast majority of the records. (en)
Title
  • Novel Nature Inspired Techniques in Medical Data Mining
  • Novel Nature Inspired Techniques in Medical Data Mining (en)
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  • Novel Nature Inspired Techniques in Medical Data Mining
  • Novel Nature Inspired Techniques in Medical Data Mining (en)
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  • RIV/68407700:21230/11:00203370!RIV13-MSM-21230___
http://linked.open...avai/predkladatel
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  • Z(MSM6840770012)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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  • 216598
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  • RIV/68407700:21230/11:00203370
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  • Swarm Intelligence; Ant Colony; Text Mining; Data Mining; Medical Record Processing (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [43B8B03CB49B]
http://linked.open...in/vavai/riv/obor
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http://linked.open...UplatneniVysledku
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  • Burša, Miroslav
  • Lhotská, Lenka
http://linked.open...n/vavai/riv/zamer
http://bibframe.org/vocab/doi
  • 10.1016/j.procs.2011.09.079
http://localhost/t...ganizacniJednotka
  • 21230
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