This abstract provides a short overview of the first edition of the shared task on Personalised Information Retrieval (PIR) organized at the 16th Forum for Information Retrieval Evaluation (FIRE 2024). A more detailed discussion of the approaches used by the participating teams is available in the track overview paper. PIR 2024 consisted of two sub-tasks. The first sub-task aims to explore the personalisation in cQA based on user profiles, following the standard IR pipeline. The second one, instead, aims to investigate the personalisation in cQA based on user profiles using recent LLMs and prompt engineering. Although the tasks saw an enthusiastic response in registrations, with 10 teams requesting the dataset, only 1 team finally submitted the runs, and 2 of them submitted the working notes.
Kasela, P., Braga, M., Sokli, E., Milanese, G., Peikos, G., Modha, S., et al. (2025). Overview of the PIR Track at FIRE 2024: Evaluation of Personalised Information Retrieval. In FIRE '24: Proceedings of the 16th Annual Meeting of the Forum for Information Retrieval Evaluation (pp.11-13). Association for Computing Machinery [10.1145/3734947.3735665].
Overview of the PIR Track at FIRE 2024: Evaluation of Personalised Information Retrieval
Kasela P.;Braga M.;Sokli E.;Milanese G. C.;Peikos G.;Modha S.;Raganato A.;Viviani M.;Pasi G.
2025
Abstract
This abstract provides a short overview of the first edition of the shared task on Personalised Information Retrieval (PIR) organized at the 16th Forum for Information Retrieval Evaluation (FIRE 2024). A more detailed discussion of the approaches used by the participating teams is available in the track overview paper. PIR 2024 consisted of two sub-tasks. The first sub-task aims to explore the personalisation in cQA based on user profiles, following the standard IR pipeline. The second one, instead, aims to investigate the personalisation in cQA based on user profiles using recent LLMs and prompt engineering. Although the tasks saw an enthusiastic response in registrations, with 10 teams requesting the dataset, only 1 team finally submitted the runs, and 2 of them submitted the working notes.
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