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In triadic data setting, implications can be extracted in different forms: those introduced by Biedermann (conditional attribute and attributional condition implications) and those introduced by Ganter and Obiedkov (attribute \(\times \) condition, conditional attribute and attributional condition implications). We provide in this paper an optimal set of implications for triadic data, based on pseudo-features, a notion similar to pseudo-intent for dyadic data.

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An Optimal Set of Implications in Triadic Contexts

  • 会议论文

  • 发表日期：

    2025年

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  • Romuald Kwessy Mouona,
  • Blaise Blériot Koguep Njionou,
  • Leonard Kwuida,
  • Etienne Romuald Temgoua Alomo

摘要

In triadic data setting, implications can be extracted in different forms: those introduced by Biedermann (conditional attribute and attributional condition implications) and those introduced by Ganter and Obiedkov (attribute \(\times \) condition, conditional attribute and attributional condition implications). We provide in this paper an optimal set of implications for triadic data, based on pseudo-features, a notion similar to pseudo-intent for dyadic data.