This paper is intended to be a report of the work we have done for the CLEF 2023 LongEval Lab, whose main goal is to evaluate and improve performances of IR models along time. We have implemented a basic retrieval system and then modified and extended it, focusing on different query expansion techniques, involving the use of synonyms and pseudo-relevance feedback. We will provide a description of our ideas, code and other development details, along with statistical analysis of the runs of our systems on different test collections.
SEUPD@CLEF: RAFJAM on Longitudinal Evaluation of Model Performance
Ferro N.
2023
Abstract
This paper is intended to be a report of the work we have done for the CLEF 2023 LongEval Lab, whose main goal is to evaluate and improve performances of IR models along time. We have implemented a basic retrieval system and then modified and extended it, focusing on different query expansion techniques, involving the use of synonyms and pseudo-relevance feedback. We will provide a description of our ideas, code and other development details, along with statistical analysis of the runs of our systems on different test collections.File in questo prodotto:
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