Information Access In The Era Of Generative Ai

Information Access in the Era of Generative AI

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, the sociotechnical implications of GenAI for information access, 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.

Advances in Information Retrieval

The five-volume set LNCS 15572, 15573, 15574, 15575 and 15576 constitutes the refereed conference proceedings of the 47th European Conference on Information Retrieval, ECIR 2025, held in Lucca, Italy, during April 6–10, 2025. The 52 full papers, 11 findings, 42 short papers and 76 papers of other types presented in these proceedings were carefully reviewed and selected from 530 submissions. The accepted papers cover the state-of-the-art in information retrieval and recommender systems: user aspects, system and foundational aspects, artificial intelligence and machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search and recommendation.

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