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This paper presents the method Wave Top-k Random-d Family Search (WTRFS) which guides an expert through data mining results according to her interest. The method exploits expert feedback, paired with the relation between patterns to spread the expert’s interest. It avoids the typical feature definition step commonly used in interactive data mining which limits the flexibility of the discovery process. We empirically demonstrate that WTRFS returns the most relevant results for the user’s subjective interest. Even with imperfect feedback, WTRFS behavior is robust as it stills deliver primarily most interesting results.

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Wave Top-k Random-d Family Search: How to Guide an Expert in a Structured Pattern Space

  • 会议论文

  • 发表日期：

    2025年

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  • Etienne Lehembre,
  • Bruno Cremilleux,
  • Bertrand Cuissart,
  • Abdelkader Ouali,
  • Albrecht Zimmermann

摘要

This paper presents the method Wave Top-k Random-d Family Search (WTRFS) which guides an expert through data mining results according to her interest. The method exploits expert feedback, paired with the relation between patterns to spread the expert’s interest. It avoids the typical feature definition step commonly used in interactive data mining which limits the flexibility of the discovery process. We empirically demonstrate that WTRFS returns the most relevant results for the user’s subjective interest. Even with imperfect feedback, WTRFS behavior is robust as it stills deliver primarily most interesting results.