Authors:
- Explains the benefits of heterogeneous information networks for readers
- Offers readers an understanding of developing trends in social network analysis
- Provides a comprehensive survey of current developments of heterogeneous information networks
- Includes supplementary material: sn.pub/extras
Part of the book series: Data Analytics (DAANA)
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Table of contents (9 chapters)
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Front Matter
About this book
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 orpattern recognition.
Authors and Affiliations
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Beijing University of Posts and Telecommunications, Beijing, China
Chuan Shi
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University of Illinois at Chicago, Chicago, USA
Philip S. Yu
Bibliographic Information
Book Title: Heterogeneous Information Network Analysis and Applications
Authors: Chuan Shi, Philip S. Yu
Series Title: Data Analytics
DOI: https://doi.org/10.1007/978-3-319-56212-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-56211-7Published: 01 June 2017
Softcover ISBN: 978-3-319-85855-5Published: 02 August 2018
eBook ISBN: 978-3-319-56212-4Published: 25 May 2017
Series ISSN: 2520-1859
Series E-ISSN: 2520-1867
Edition Number: 1
Number of Pages: IX, 227
Number of Illustrations: 9 b/w illustrations, 53 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Artificial Intelligence, Pattern Recognition, Communications Engineering, Networks, Computer Communication Networks