Heterogeneous Information Network Analysis and Applications

  • Chuan Shi
  • Philip S. Yu
Part of the Data Analytics book series (DAANA)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Chuan Shi, Philip S. Yu
    Pages 1-11
  3. Chuan Shi, Philip S. Yu
    Pages 13-30
  4. Chuan Shi, Philip S. Yu
    Pages 31-60
  5. Chuan Shi, Philip S. Yu
    Pages 61-96
  6. Chuan Shi, Philip S. Yu
    Pages 97-141
  7. Chuan Shi, Philip S. Yu
    Pages 143-180
  8. Chuan Shi, Philip S. Yu
    Pages 181-199
  9. Chuan Shi, Philip S. Yu
    Pages 201-217
  10. Chuan Shi, Philip S. Yu
    Pages 219-227

About this book

Introduction

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. 




Keywords

Heterogeneous information network Social networks Social network analysis Networked data Homogeneous information network Data mining Machine learning Similarity search Ranking Clustering Recommendation Meta path Network schema

Authors and affiliations

  • Chuan Shi
    • 1
  • Philip S. Yu
    • 2
  1. 1.Beijing University of Posts and TelecommunicationsBeijingChina
  2. 2.University of Illinois at ChicagoChicagoUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-56212-4
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-56211-7
  • Online ISBN 978-3-319-56212-4
  • Series Print ISSN 2520-1859
  • Series Online ISSN 2520-1867
  • About this book