SEUPD@CLEF: Team DAM on Reranking Using Sentence Embedders

Alberto Basaglia, Andrea Stocco, Milica Popović, Nicola Ferro

Research output: Contribution to journalConference articlepeer-review

Abstract

This report gives an overview of the system developed by Team DAM for Task 1 of the LongEval Lab at CLEF 2024. The team members are students enrolled in the Computer Engineering master's program at the University of Padua. The team developed an information retrieval system which is then used to perform queries on a corpus of documents in French language, or in their translated English version.

Original languageEnglish
Pages (from-to)2314-2335
Number of pages22
JournalCEUR Workshop Proceedings
Volume3740
StatePublished - 2024
Externally publishedYes
Event25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024 - Grenoble, France
Duration: 9 Sep 202412 Sep 2024

Keywords

  • CLEF
  • Documents Retrieval
  • Information Retrieval
  • LongEval 2024
  • Reranking
  • Search Engine
  • Temporal Persistence
  • Word Embeddings

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