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Engineering information systems with large language models

Record Type:	Electronic resources : Monograph/item
Title/Author:	Engineering information systems with large language models/ edited by Francesca De Luzi, Flavia Monti, Massimo Mecella.
other author:	De Luzi, Francesca.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xiii, 283 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	1. Introduction -- 2. History of LLMs -- 3. LLMs for Dummies -- 4. A Reference Framework for Information Systems -- 5. Exploring Large Language Models in Information Systems: A Survey -- 6. Programming LLMs -- 7. Retrieval Augmented Generation -- 8. Large Language Model Agents -- 9. Applications of Large Language Models in Information Systems -- 10. Ethics and Governance of Large Language Models -- 11. Epilogue.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence. -
Online resource:	https://doi.org/10.1007/978-3-031-92285-5
ISBN:	9783031922855

Engineering information systems with large language models
Engineering information systems with large language models[electronic resource] /edited by Francesca De Luzi, Flavia Monti, Massimo Mecella. - Cham :Springer Nature Switzerland :2025. - xiii, 283 p. :ill. (some col.), digital ;24 cm.

1. Introduction -- 2. History of LLMs -- 3. LLMs for Dummies -- 4. A Reference Framework for Information Systems -- 5. Exploring Large Language Models in Information Systems: A Survey -- 6. Programming LLMs -- 7. Retrieval Augmented Generation -- 8. Large Language Model Agents -- 9. Applications of Large Language Models in Information Systems -- 10. Ethics and Governance of Large Language Models -- 11. Epilogue.

The rapid advancement of generative AI and specifically large language models (LLMs) is transforming the landscape of information systems (IS) engineering by offering unprecedented opportunities to support their design, development, maintenance, and reengineering. Starting with an overview of LLM history and foundational concepts, the book delves into practical applications for IS design and development, including prompt engineering, retrieval augmented generation, and multi-agent systems. Through a detailed survey and step-by-step programming guidance, readers will learn how to implement tools leveraging LLMs effectively. The book also addresses ethical considerations, offering insights and guidelines for responsible AI integration. The book provides a comprehensive and unified framework for exploiting LLMs in IS engineering. It aims at both researchers in information systems or LLM development and advanced professionals who would like to know how to potentially apply LLMs in the development or maintenance of information systems.

ISBN: 9783031922855

Standard No.: 10.1007/978-3-031-92285-5doiSubjects--Topical Terms:

516317
Artificial intelligence.

LC Class. No.: Q335

Dewey Class. No.: 006.3

Engineering information systems with large language models
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245 0 0 $a Engineering information systems with large language models $h [electronic resource] / $c edited by Francesca De Luzi, Flavia Monti, Massimo Mecella.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xiii, 283 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 1. Introduction -- 2. History of LLMs -- 3. LLMs for Dummies -- 4. A Reference Framework for Information Systems -- 5. Exploring Large Language Models in Information Systems: A Survey -- 6. Programming LLMs -- 7. Retrieval Augmented Generation -- 8. Large Language Model Agents -- 9. Applications of Large Language Models in Information Systems -- 10. Ethics and Governance of Large Language Models -- 11. Epilogue.
520 $a The rapid advancement of generative AI and specifically large language models (LLMs) is transforming the landscape of information systems (IS) engineering by offering unprecedented opportunities to support their design, development, maintenance, and reengineering. Starting with an overview of LLM history and foundational concepts, the book delves into practical applications for IS design and development, including prompt engineering, retrieval augmented generation, and multi-agent systems. Through a detailed survey and step-by-step programming guidance, readers will learn how to implement tools leveraging LLMs effectively. The book also addresses ethical considerations, offering insights and guidelines for responsible AI integration. The book provides a comprehensive and unified framework for exploiting LLMs in IS engineering. It aims at both researchers in information systems or LLM development and advanced professionals who would like to know how to potentially apply LLMs in the development or maintenance of information systems.
650 0 $a Artificial intelligence. $3 516317
650 0 $a Artificial intelligence $x Moral and ethical aspects. $3 961670
650 0 $a Systems engineering. $3 572511
650 1 4 $a Computer and Information Systems Applications. $3 3538505
650 2 4 $a Business Information Systems. $3 892640
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a De Luzi, Francesca. $3 3789982
700 1 $a Monti, Flavia. $3 3668822
700 1 $a Mecella, Massimo. $3 1244286
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-92285-5
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