Heterogeneous Information Network Analysis and Applications
| AUTHOR | Yu, Philip S.; Shi, Chuan |
| PUBLISHER | Springer (06/01/2017) |
| PRODUCT TYPE | Hardcover (Hardcover) |
Description
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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Product Format
Product Details
ISBN-13:
9783319562117
ISBN-10:
3319562118
Binding:
Hardback or Cased Book (Sewn)
Content Language:
English
More Product Details
Page Count:
227
Carton Quantity:
30
Product Dimensions:
6.14 x 0.56 x 9.21 inches
Weight:
1.13 pound(s)
Feature Codes:
Illustrated
Country of Origin:
NL
Subject Information
BISAC Categories
Computers | Data Science - Data Analytics
Computers | Artificial Intelligence - Computer Vision & Pattern Recognit
Computers | Telecommunications
Dewey Decimal:
004.6
Descriptions, Reviews, Etc.
publisher marketing
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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List Price $159.99
Your Price
$158.39