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 Retriev...

সম্পূর্ণ বিবরণ

সংরক্ষণ করুন:
গ্রন্থ-পঞ্জীর বিবরন
সংস্থা লেখক: SpringerLink (Online service)
অন্যান্য লেখক: White, Ryen W. (Editor), Shah, Chirag (Editor)
বিন্যাস: বৈদ্যুতিক বৈদ্যুতিন গ্রন্থ
ভাষা:ইংরেজি
প্রকাশিত: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
সংস্করন:1st ed. 2025.
মালা:The Information Retrieval Series, 51
বিষয়গুলি:
অনলাইন ব্যবহার করুন:https://doi.org/10.1007/978-3-031-73147-1
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MARC

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505 0 |a 1. Introduction -- 2. Foundations of Generative IR -- 3. Interactions With Generative IR Systems -- 4. Adapting Generative IR Systems to Users, Tasks, and Scenarios -- 5. Improving Generative IR Systems Based on User Feedback -- 6. Generative IR Evaluation -- 7. Sociotechnical Implications of Generative AI for Information Access -- 8. Recommendation in the Era of Generative AI -- 9. Designing for the Future of Information Access with Generative IR. 
520 |a 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. 
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