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pro vyhledávání: '"information retrieval evaluation"'
Information Retrieval (IR) systems are exposed to constant changes in most components. Documents are created, updated, or deleted, the information needs are changing, and even relevance might not be static. While it is generally expected that the IR
Externí odkaz:
http://arxiv.org/abs/2409.05417
The traditional evaluation of information retrieval (IR) systems is generally very costly as it requires manual relevance annotation from human experts. Recent advancements in generative artificial intelligence -- specifically large language models (
Externí odkaz:
http://arxiv.org/abs/2407.02464
This paper is a draft of a chapter intended to appear in a forthcoming book on generative information retrieval, co-edited by Chirag Shah and Ryen White. In this chapter, we consider generative information retrieval evaluation from two distinct but i
Externí odkaz:
http://arxiv.org/abs/2404.08137
Autor:
Joseph, Minnu Helen, Ravana, Sri Devi sdevi@um.edu.my
Publikováno v:
Information Research. 2024, Vol. 29 Issue 3, p109-131. 23p. 2 Diagrams, 3 Charts, 7 Graphs.
Autor:
Giner, Fernando
Publikováno v:
LNNS 822 (2024) 692-713
Information retrieval (IR) evaluation measures are cornerstones for determining the suitability and task performance efficiency of retrieval systems. Their metric and scale properties enable to compare one system against another to establish differen
Externí odkaz:
http://arxiv.org/abs/2304.00615
Autor:
Breuer, Timo, Tavakolpoursaleh, Narges, Schaible, Johann, Hienert, Daniel, Schaer, Philipp, Castro, Leyla Jael
Publikováno v:
Information Retrieval Meeting (IRM 2022)
Involving users in early phases of software development has become a common strategy as it enables developers to consider user needs from the beginning. Once a system is in production, new opportunities to observe, evaluate and learn from users emerg
Externí odkaz:
http://arxiv.org/abs/2210.13202
Akademický článek
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Publikováno v:
Journal of the Association for Information Science and Technology (2022)1-13
With the emerging needs of creating fairness-aware solutions for search and recommendation systems, a daunting challenge exists of evaluating such solutions. While many of the traditional information retrieval (IR) metrics can capture the relevance,
Externí odkaz:
http://arxiv.org/abs/2106.08527