Heterogeneous Information Network Analysis and Applications

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Database Management, General Computing
Cover of the book Heterogeneous Information Network Analysis and Applications by Chuan Shi, Philip S. Yu, Springer International Publishing
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Author: Chuan Shi, Philip S. Yu ISBN: 9783319562124
Publisher: Springer International Publishing Publication: May 25, 2017
Imprint: Springer Language: English
Author: Chuan Shi, Philip S. Yu
ISBN: 9783319562124
Publisher: Springer International Publishing
Publication: May 25, 2017
Imprint: Springer
Language: English

This book offers researchers an understanding of the fundamental issues and a good starting point to work on this rapidly expanding field. It provides a comprehensive survey of current developments of heterogeneous information network. It also presents the newest research in applications of heterogeneous information networks to similarity search, ranking, clustering, recommendation. 

This information will help researchers to understand how to analyze networked data with heterogeneous information networks. Common data mining tasks are explored, including similarity search, ranking, and recommendation. The book illustrates some prototypes which analyze networked data.

Professionals and academics working in data analytics, networks, machine learning, and data mining will find this content valuable. It is also suitable for advanced-level students in computer science who are interested in networking or pattern recognition. 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book offers researchers an understanding of the fundamental issues and a good starting point to work on this rapidly expanding field. It provides a comprehensive survey of current developments of heterogeneous information network. It also presents the newest research in applications of heterogeneous information networks to similarity search, ranking, clustering, recommendation. 

This information will help researchers to understand how to analyze networked data with heterogeneous information networks. Common data mining tasks are explored, including similarity search, ranking, and recommendation. The book illustrates some prototypes which analyze networked data.

Professionals and academics working in data analytics, networks, machine learning, and data mining will find this content valuable. It is also suitable for advanced-level students in computer science who are interested in networking or pattern recognition. 

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