Recommender systems [electronic resource] : advanced developments / Jie Lu, Qian Zhang, Guangquan Zhang.
- 作者： Lu, Jie.
- 其他作者：
- 其他題名：
- Intelligent information systems ;
- 出版： Singapore : World Scientific c2021.
- 叢書名： Intelligent information systems ;v. 6
- 主題： Recommender systems (Information filtering) , Personal communication service systems.
- 版本：1st ed.
- ISBN： 9789811224638 (ebook) 、 9789811224645 (ebook)
- URL：
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- 一般註：Recommender systems : introduction. Recommender system concepts. Basic recommendation methods. Recommender system applications -- Recommender systems : methods and algorithms. Social network-based recommender systems. Tag-aware recommender systems. Fuzzy technique-enhanced recommender systems. Tree similarity-based recommender systems. Group recommender systems. Cross-domain recommender systems. User preference drift-aware recommender systems. Visualization in recommender systems -- Recommender systems : software and applications. Telecom products/services recommender systems. Recommender system for small and medium-sized businesses finding business partners. Recommender system for personalized e-learning. Recommender system for real estate property investment. 110年度臺灣學術電子書暨資料庫聯盟採購
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讀者標籤：
- 系統號： 000289287 | 機讀編目格式
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摘要註
"Recommender systems provide users (businesses or individuals) with personalized online recommendations of products or information, to address the problem of information overload and improve personalized services. Recent successful applications of recommender systems are providing solutions to transform online services for e-government, e-business, e-commerce, e-shopping, e-library, e-learning, e-tourism, and more. This unique compendium not only describes theoretical research but also reports on new application developments, prototypes, and real-world case studies of recommender systems. The comprehensive volume provides readers with a timely snapshot of how new recommendation methods and algorithms can overcome challenging issues. Furthermore, the monograph systematically presents three dimensions of recommender systems - basic recommender system concepts, advanced recommender system methods, and real-world recommender system applications. By providing state-of-the-art knowledge, this excellent reference text will immensely benefit researchers, managers, and professionals in business, government, and education to understand the concepts, methods, algorithms and application developments in recommender systems"--Publisher's website.