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Recommender systemsadvanced developm...

Lu, Jie.

Recommender systemsadvanced developments /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Recommender systemsJie Lu, Qian Zhang, Guangquan Zhang.
Reminder of title:	advanced developments /
Author:	Lu, Jie.
other author:	Zhang, Qian.
Published:	Singapore :World Scientific,c2021.
Description:	1 online resource (xxii, 339 p.)
Subject:	Recommender systems (Information filtering)
Online resource:	https://www.worldscientific.com/worldscibooks/10.1142/11947#t=toc
ISBN:	9789811224638$q(ebook)

Recommender systemsadvanced developments /
Lu, Jie.

Recommender systemsadvanced developments /[electronic resource] :Jie Lu, Qian Zhang, Guangquan Zhang. - 1st ed. - Singapore :World Scientific,c2021. - 1 online resource (xxii, 339 p.) - Intelligent information systems ;v. 6. - Intelligent information systems ;v. 3..

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.

"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.

Mode of access: World Wide Web.

ISBN: 9789811224638$q(ebook)Subjects--Topical Terms:

310886
Recommender systems (Information filtering)

LC Class. No.: TK5103.485 / .L8 2021

Dewey Class. No.: 006.33

Recommender systemsadvanced developments /
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245 1 0 $a Recommender systems $h [electronic resource] : $b advanced developments / $c Jie Lu, Qian Zhang, Guangquan Zhang.
250 $a 1st ed.
260 $a Singapore : $b World Scientific, $c c2021.
300 $a 1 online resource (xxii, 339 p.)
490 1 $a Intelligent information systems ; $v v. 6
505 0 $a 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.
520 $a "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.
538 $a Mode of access: World Wide Web.
538 $a System requirements: Adobe Acrobat Reader.
588 $a Description based on print version record.
650 0 $a Recommender systems (Information filtering) $3 310886
650 0 $a Personal communication service systems. $3 182332
700 1 $a Zhang, Qian. $3 678380
700 1 $a Zhang, Guangquan. $3 379745
830 0 $a Intelligent information systems ; $v v. 3. $3 575614
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/11947#t=toc