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We examine the influence of Arno Siebes’s work on various data mining researchers in Rennes, France. A substantial aspect of this impact revolves around the Minimum Description Length Principle and its role in extracting a concise set of meaningful patterns from datasets. In Rennes, these patterns include (nested) itemsets, periodic itemsets, subsequences, and graphs. After briefly presenting the methods developed in our lab, we illustrate their application using datasets related to Arno’s life and experiences.

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The Minimum Description of Arno’s Legacy in Rennes

  • 章节

  • 发表日期：

    2026年

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  • Peggy Cellier,
  • Sébastien Ferré,
  • Elisa Fromont,
  • Luis Galárraga,
  • Alexandre Termier

摘要

We examine the influence of Arno Siebes’s work on various data mining researchers in Rennes, France. A substantial aspect of this impact revolves around the Minimum Description Length Principle and its role in extracting a concise set of meaningful patterns from datasets. In Rennes, these patterns include (nested) itemsets, periodic itemsets, subsequences, and graphs. After briefly presenting the methods developed in our lab, we illustrate their application using datasets related to Arno’s life and experiences.