White / Shah

Information Access in the Era of Generative AI

Springer

ISBN 978-3-031-73146-4

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181,89 €

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auch verfügbar als eBook (PDF) für 171,19 €

Bibliografische Daten

Fachbuch

Buch. Hardcover

2024

4 s/w-Abbildungen, 22 Farbabbildungen, Bibliographien.

In englischer Sprache

Umfang: ix, 248 S.

Format (B x L): 15,5 x 23,5 cm

Verlag: Springer

ISBN: 978-3-031-73146-4

Weiterführende bibliografische Daten

Das Werk ist Teil der Reihe: The Information Retrieval Series; 51

auch verfügbar als eBook (PDF) für 171,19 €

Produktbeschreibung

Generative Artificial Intelligence (GenAI) has emerged as a groundbreaking technology that promises to revolutionize many industries as well as people’s personal and professional lives. This book discusses GenAI and its role in information access - often referred to as Generative Information Retrieval (GenIR) - or more broadly, information interaction. The role of GenAI in information access is complex and dynamic, with many dimensions. To address this, following a brief introduction to GenAI and GenIR, the remainder of the book provides eight chapters, each targeting a different dimension or sub-topic. These cover foundations of GenIR, interactions with GenIR systems, adapting them to users, tasks, and scenarios, improving them based on user feedback, GenIR evaluation, sociotechnical implications of GenAI, recommendations within GenIR, and the future of information access with GenIR. The book is targeted at graduate students and researchers interested in issues of information retrieval, access, and interactions, as well as applications of GenAI in various informational contexts. While some of the parts assume prior background in IR or AI, most others do not, making this book suitable for adoption in various classes as a primary source or as a supplementary material.

Autorinnen und Autoren

Kundeninformationen

Discusses GenAI and its many dimensions in information access and interaction Covers GenAI/GenIR foundations, interactions, evaluations, sociotechnical implications and recommendations Targeted at researchers and graduate students in information retrieval or GenAI applications

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