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Heterogeneous Information Network Analysis and Applications: Data Analytics

Autor Chuan Shi, Philip S. Yu
en Limba Engleză Paperback – 2 aug 2018
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 orpattern recognition. 




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Specificații

ISBN-13: 9783319858555
ISBN-10: 3319858556
Ilustrații: IX, 227 p. 62 illus., 53 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.34 kg
Ediția:Softcover reprint of the original 1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seria Data Analytics

Locul publicării:Cham, Switzerland

Cuprins

1. Introduction.- 2. Summarization of the developments.- 3.Uniform relevance measure of heterogeneous objects.- 4. Path based Ranking.- 5. Ranking based Clustering.- 6. Recommendation with heterogeneous information.- 7.  Information fusion with heterogeneous network.- 8. Prototype system.- 9. Future research directions.- 10. Conclusion.

Caracteristici

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