Next-Generation Recommendation Systems: A Comprehensive Guide to Enabling Technologies and Tools and Their Business Benefits
暫譯: 下一代推薦系統:啟用技術與工具及其商業效益的全面指南

Chelliah, Pethuru Raj, Blessie, E. Chandra, Sundaravadivazhagan, B.

  • 出版商: Wiley
  • 出版日期: 2026-07-01
  • 售價: $4,260
  • 貴賓價: 9.5$4,047
  • 語言: 英文
  • 頁數: 624
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1394351542
  • ISBN-13: 9781394351541
  • 相關分類: 推薦系統
  • 尚未上市,無法訂購

商品描述

A detailed guide to building cutting-edge recommendation systems

In Next-Generation Recommendation Systems: A Comprehensive Guide to Enabling Technologies and Tools and their Business Benefits, a team of experienced technologists and educators, each with a proven track record in the field, delivers an expert guide to building robust recommendation systems that can interface with complex databases. The authors' deep understanding of the subject matter is evident as they explain how to use the latest AI technologies, including LLMs, graph neural networks, diffusion models, and generative adversarial networks, to create recommendation engines that users enjoy and that drive business revenue.

The book does not just delve into theoretical concepts, but also connects them to advanced implementation techniques. It demonstrates the application of practical and adaptable techniques, such as graph embeddings and Bayesian networks, to solve real-world problems faced by platform users and businesses. Readers will find the knowledge and tools to tackle these challenges head-on.

  • Comprehensive coverage of practical generative AI techniques, including large language models and diffusion models
  • Detailed exploration of graph neural networks and knowledge graph embeddings to solve common recommendation engine problems
  • Practical guidance on implementing generative adversarial networks and variational autoencoders to address mode collapse and information bottleneck challenges
  • In-depth analysis of hybrid recommendation architectures that combine content-based, collaborative, and knowledge-based filtering

Real-world deployment strategies using cloud-native computing environments are not just theoretical concepts in this book. They are actionable strategies that have been tested and proven effective. This emphasis on real-world applicability will reassure readers about the book's relevance to their professional or academic pursuits.

Perfect for data scientists, AI specialists, software engineers, architects, and graduate students, Next-Generation Recommendation Systems is an essential, up-to-date resource for everyone involved in the design, deployment, and optimization of recommendation systems that connect to large, complex datasets.

商品描述(中文翻譯)

建構尖端推薦系統的詳細指南
下一代推薦系統:啟用技術與工具及其商業利益的綜合指南中,一組經驗豐富的技術專家和教育者,皆在該領域擁有良好記錄,提供了一本專家指南,幫助建立能夠與複雜數據庫接口的穩健推薦系統。作者對主題的深刻理解在於他們解釋如何使用最新的人工智慧技術,包括大型語言模型(LLMs)、圖神經網絡、擴散模型和生成對抗網絡,來創建用戶喜愛且能推動商業收入的推薦引擎。
這本書不僅深入探討理論概念,還將其與先進的實施技術相連結。它展示了實用且可適應的技術應用,例如圖嵌入和貝葉斯網絡,以解決平台用戶和企業面臨的現實問題。讀者將獲得應對這些挑戰的知識和工具。


  • 全面涵蓋實用的生成式人工智慧技術,包括大型語言模型和擴散模型

  • 詳細探討圖神經網絡和知識圖嵌入,以解決常見的推薦引擎問題

  • 提供實用指導,實施生成對抗網絡和變分自編碼器,以應對模式崩潰和信息瓶頸挑戰

  • 深入分析結合內容基礎、協作和知識基礎過濾的混合推薦架構


使用雲原生計算環境的現實部署策略在這本書中不僅是理論概念,而是經過測試並證明有效的可行策略。這種對現實應用性的強調將使讀者對本書在其專業或學術追求中的相關性感到安心。
下一代推薦系統非常適合數據科學家、人工智慧專家、軟體工程師、架構師和研究生,是所有參與設計、部署和優化連接大型複雜數據集的推薦系統的人的必備、最新資源。

作者簡介

Pethuru Raj Chelliah, PhD, is Principal AI Architect in Infocion Inc., Bangalore

E. Chandra Blessie, PhD, is an Associate Professor in the Department of Computing (Artificial et al.) at the Coimbatore Institute of Technology.

B. Sundaravadivazhagan, PhD, is an information and communications engineering researcher and educator.

Preetha Evangeline, PhD, is an experienced educator and expert in data structures, operating systems, and high-performance computing.

作者簡介(中文翻譯)

Pethuru Raj Chelliah, PhD, 是位於班加羅爾的Infocion Inc.的首席人工智慧架構師。

E. Chandra Blessie, PhD, 是科印巴托技術學院計算系(人工智慧等)的副教授。

B. Sundaravadivazhagan, PhD, 是一位資訊與通信工程的研究者和教育者。

Preetha Evangeline, PhD, 是一位經驗豐富的教育者,專精於資料結構、作業系統和高效能計算。