Recommender Systems: Algorithms and Applications
暫譯: 推薦系統：演算法與應用
Pavan Kumar, P., Vairachilai, S., Potluri, Sirisha
- 出版商: CRC
- 出版日期: 2021-06-04
- 售價: $4,590
- 貴賓價: 9.5 折 $4,361
- 語言: 英文
- 頁數: 230
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 0367631857
- ISBN-13: 9780367631857
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相關分類:
推薦系統、Algorithms-data-structures
海外代購書籍(需單獨結帳)
商品描述
Recommender systems use information filtering to predict user preferences. They are becoming a vital part of e-business and are used in a wide variety of industries, ranging from entertainment and social networking to information technology, tourism, education, agriculture, healthcare, manufacturing, and retail. Recommender Systems: Algorithms and Applications dives into the theoretical underpinnings of these systems and looks at how this theory is applied and implemented in actual systems.
The book examines several classes of recommendation algorithms, including
- Machine learning algorithms
- Community detection algorithms
- Filtering algorithms
Various efficient and robust product recommender systems using machine learning algorithms are helpful in filtering and exploring unseen data by users for better prediction and extrapolation of decisions. These are providing a wider range of solutions to such challenges as imbalanced data set problems, cold-start problems, and long tail problems. This book also looks at fundamental ontological positions that form the foundations of recommender systems and explain why certain recommendations are predicted over others.
Techniques and approaches for developing recommender systems are also investigated. These can help with implementing algorithms as systems and include
- A latent-factor technique for model-based filtering systems
- Collaborative filtering approaches
- Content-based approaches
Finally, this book examines actual systems for social networking, recommending consumer products, and predicting risk in software engineering projects.
商品描述(中文翻譯)
推薦系統使用資訊過濾技術來預測用戶偏好。它們正逐漸成為電子商務的重要組成部分，並在娛樂、社交網絡、資訊科技、旅遊、教育、農業、醫療保健、製造業和零售等各個行業中廣泛應用。《推薦系統：演算法與應用》深入探討了這些系統的理論基礎，並研究了這些理論如何在實際系統中應用和實現。
本書考察了幾類推薦演算法，包括：
- 機器學習演算法
- 社群偵測演算法
- 過濾演算法
各種使用機器學習演算法的高效且穩健的產品推薦系統，有助於過濾和探索用戶未見過的數據，以便更好地預測和推斷決策。這些系統提供了更廣泛的解決方案，以應對不平衡數據集問題、冷啟動問題和長尾問題。本書還探討了構成推薦系統基礎的基本本體論立場，並解釋為什麼某些推薦會被預測而非其他推薦。
本書還調查了開發推薦系統的技術和方法，這些方法有助於將演算法實現為系統，包括：
- 用於基於模型的過濾系統的潛在因子技術
- 協同過濾方法
- 基於內容的方法
最後，本書考察了社交網絡、推薦消費產品和預測軟體工程項目風險的實際系統。
作者簡介
Dr. P. Pavan Kumar received a Ph.D. degree from JNTU, Anantapur, India. He is an Assistant Professor in the Department of Computer Science and Engineering at ICFAI Foundation for Higher Education (IFHE), Hyderabad. His research interests include real-time systems, multi-core systems, high-performance systems, computer vision.
Dr. S. Vairachilai earned a Ph.D. degree in Information Technology from Anna University, India. She is an Assistant Professor in the Department of CSE at ICFAI Foundation for Higher Education (IFHE), Hyderabad, Telangana. Prior to this she served in teaching roles an Kalasalingam University and N.P.R College of Engineering and Technology, Tamilnadu, India. Her research interests include Machine Learning, Recommender System and Social Network Analysis.
Sirisha Potluri is an Assistant Professor in the Department of Computer Science & Engineering at ICFAI Foundation for Higher Education, Hyderabad. She is pursuing a Ph.D. degree in the area of cloud computing. Her research areas include distributed computing, cloud computing, fog computing, recommender systems and IoT.
Dr. Sachi Nandan Mohanty received a Ph.D. degree from IIT Kharagpur, India. He is an Associate Professor in the Department of Computer Science & Engineering at ICFAI Foundation for Higher Education Hyderabad. Prof. Mohanty's research areas include data mining, big data analysis, cognitive science, fuzzy decision making, brain-computer interface, and computational intelligence.
作者簡介(中文翻譯)
Dr. P. Pavan Kumar 於印度安納塔布爾的 JNTU 獲得博士學位。他是海得拉巴 ICFAI 高等教育基金會 (IFHE) 計算機科學與工程系的助理教授。他的研究興趣包括即時系統、多核心系統、高效能系統和計算機視覺。
Dr. S. Vairachilai 於印度安娜大學獲得資訊科技博士學位。她是海得拉巴 ICFAI 高等教育基金會 (IFHE) 計算機科學與工程系的助理教授。在此之前，她曾在印度泰米爾納德邦的 Kalasalingam 大學和 N.P.R 工程與技術學院擔任教學職位。她的研究興趣包括機器學習、推薦系統和社交網絡分析。
Sirisha Potluri 是海得拉巴 ICFAI 高等教育基金會計算機科學與工程系的助理教授。她正在追求雲計算領域的博士學位。她的研究領域包括分散式計算、雲計算、霧計算、推薦系統和物聯網。
Dr. Sachi Nandan Mohanty 於印度 IIT Kharagpur 獲得博士學位。他是海得拉巴 ICFAI 高等教育基金會計算機科學與工程系的副教授。Mohanty 教授的研究領域包括資料探勘、大數據分析、認知科學、模糊決策、腦機介面和計算智能。
