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Many components of information retrieval systems evolve over time. The LongEval Lab aims to provide a benchmark setting to the longitudinal evaluation of IR models. At its fourth edition, LongEval we focus on scholarly search and scholarly user models. We describe in this paper the tasks that are planned for the 2026 lab, the data necessary for each of the tasks, as well as the choice of evaluation activities.

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Evaluating Information Retrieval Models Along Time: The LongEval Lab at CLEF 2026

  • 会议论文

  • 发表日期：

    2026年

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  • Timo Breuer,
  • Matteo Cancellieri,
  • Alaa El-Ebshihy,
  • Maik Fröbe,
  • Petra Galuščáková,
  • Lorraine Goeuriot,
  • Gabriel Iturra-Bocaz,
  • Jüri Keller,
  • Petr Knoth,
  • Andreas Konstantin Kruff,
  • Philippe Mulhem,
  • Florina Piroi,
  • David Pride,
  • Philipp Schaer,
  • Didier Schwab

摘要

Many components of information retrieval systems evolve over time. The LongEval Lab aims to provide a benchmark setting to the longitudinal evaluation of IR models. At its fourth edition, LongEval we focus on scholarly search and scholarly user models. We describe in this paper the tasks that are planned for the 2026 lab, the data necessary for each of the tasks, as well as the choice of evaluation activities.