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1. |
Record Nr. |
UNISA996394567803316 |
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Autore |
Milton John <1608-1674.> |
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Titolo |
Accedence commenc't grammar, supply'd with sufficient rules, for the use of such as, younger or elder, are desirous, without more trouble than needs, to attain the Latin tongue [[electronic resource] ] : the elder sort especially, with little teaching, and thir own industry. J.M |
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London, : printed for S.Simmons, next door to the Golden Lion in Aldersgate-street, 1669 |
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Descrizione fisica |
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Lingua di pubblicazione |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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J.M. = John Milton. |
Reproduction of original in the University of Illinois (Urbana-Champaign Campus). Library. |
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Sommario/riassunto |
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2. |
Record Nr. |
UNINA9910818870203321 |
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Autore |
Coccioli Emma |
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Titolo |
Animae : the invisible sources of the artwork: talks with today's artists / / Emma Coccioli |
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Pubbl/distr/stampa |
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Wilmington, Delaware ; ; Malaga, Spain : , : Vernon Press, , 2019 |
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ISBN |
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Descrizione fisica |
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1 online resource (324 pages) |
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Disciplina |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction -- Paul Benney -- Liu Bolin -- Christopher Bucklow -- Giacomo Costa. |
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3. |
Record Nr. |
UNINA9911034960403321 |
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Autore |
Wang Jianqiang (Jay) |
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Titolo |
Building recommender systems using large language models / / Jianqiang (Jay) Wang |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland, , [2025] |
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ISBN |
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9783032011527 |
3-032-01152-3 |
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Descrizione fisica |
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1 online resource (252 pages) |
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Collana |
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Professional and Applied Computing Series |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Machine learning |
Natural language processing (Computer science) |
Electronic commerce |
Intel·ligència artificial |
Aprenentatge automàtic |
Comerç electrònic |
Tractament del llenguatge natural (Informàtica) |
Artificial Intelligence |
Machine Learning |
Natural Language Processing (NLP) |
e-Commerce and e-Business |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Chapter 1 Introduction to LLMs -- Chapter 2 From Traditional to LLM-powered Recommendation Systems -- Chapter 3 LLM-enhanced recommendation system -- Chapter 4 LLM as recommendation system -- Chapter 5 Conversational recommendation systems -- Chapter 6 Leveraging Multi-Modal Data -- Chapter 7 Generative Recommendation and Planning Systems -- Chapter 8 Challenges and Trends in LLMs for Recommendation Systems. |
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Sommario/riassunto |
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This book offers a comprehensive exploration of the intersection between Large Language Models (LLMs) and recommendation systems, serving as a practical guide for practitioners, researchers, and students |
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in AI, natural language processing, and data science. It addresses the limitations of traditional recommendation techniques—such as their inability to fully understand nuanced language, reason dynamically over user preferences, or leverage multi-modal data—and demonstrates how LLMs can revolutionize personalized recommendations. By consolidating fragmented research and providing structured, hands-on tutorials, the book bridges the gap between cutting-edge research and real-world application, empowering readers to design and deploy next-generation recommender systems. Structured for progressive learning, the book covers foundational LLM concepts, the evolution from classic to LLM-powered recommendation systems, and advanced topics including end-to-end LLM recommenders, conversational agents, and multi-modal integration. Each chapter blends theoretical insights with practical coding exercises and real-world case studies, such as fashion recommendation and generative content creation. The final chapters discuss emerging challenges, including privacy, fairness, and future trends, offering a forward-looking roadmap for research and application. Readers with a basic understanding of machine learning and NLP will find this resource both accessible and invaluable for building effective, modern recommendation systems enhanced by LLMs. |
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