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pro vyhledávání: '"Kasela, Pranav"'
Open-domain question answering requires retrieval systems able to cope with the diverse and varied nature of questions, providing accurate answers across a broad spectrum of query types and topics. To deal with such topic heterogeneity through a uniq
Externí odkaz:
http://arxiv.org/abs/2403.13468
The problem of personalization in Information Retrieval has been under study for a long time. A well-known issue related to this task is the lack of publicly available datasets that can support a comparative evaluation of personalized search systems.
Externí odkaz:
http://arxiv.org/abs/2309.11686
The personalization of search results has gained increasing attention in the past few years, thanks to the development of Neural Networks-based approaches for Information Retrieval and the importance of personalization in many search scenarios. Recen
Externí odkaz:
http://arxiv.org/abs/2308.15968
Personalization in Information Retrieval is a topic studied for a long time. Nevertheless, there is still a lack of high-quality, real-world datasets to conduct large-scale experiments and evaluate models for personalized search. This paper contribut
Externí odkaz:
http://arxiv.org/abs/2306.16261
Clinical trials are a critical component of evaluating the effectiveness of new medical interventions and driving advancements in medical research. Therefore, timely enrollment of patients is crucial to prevent delays or premature termination of tria
Externí odkaz:
http://arxiv.org/abs/2306.02077
Publikováno v:
Proceedings of the 31st ACM International Conference on Information & Knowledge Management.
Personalization in Information Retrieval has been a hot topic in both academia and industry for the past two decades. However, there is still a lack of high-quality standard benchmark datasets for conducting offline comparative evaluations in this co