Evaluating Temporal Persistence of Information Retrieval Models - CLEF 2024 LongEval

Explore a detailed academic lecture examining the temporal persistence challenges in information retrieval systems through the lens of the CLEF 2024 LongEval-Retrieval Track. Dive into critical questions surrounding web search engine performance as queries and document collections evolve over time, with particular focus on determining optimal update schedules. Learn about the specialized LongEval-Retrieval collection, built using data from the French search engine Qwant, and discover key findings from the 2023 track edition. Gain insights from Associate Professor Petra Galuščáková's expertise in information retrieval and natural language processing, drawing from her extensive research experience at institutions including the University of Stavanger, University of Maryland, and University Grenoble Alpes.