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Dynamic Graph Learning for Dimension Reduction and Data Clustering

Dynamic Graph Learning for Dimension Reduction and Data Clustering - Synthesis Lectures on Computer Science

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Publisher's Synopsis

This book illustrates how to achieve effective dimension reduction and data clustering. The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of big data. The book begins by providing background on dynamic graph learning. The authors discuss why it has attracted considerable research attention in recent years and has become well recognized as an advanced technique. After covering the key topics related to dynamic graph learning, the book discusses the recent advancements in the area. The authors then explain how these techniques can be practically applied for several purposes, including feature selection, feature projection, and data clustering.

Book information

ISBN: 9783031423123
Publisher: Springer Nature Switzerland
Imprint: Springer
Pub date:
DEWEY: 005.7
DEWEY edition: 23
Language: English
Number of pages: 143
Weight: 499g
Height: 240mm
Width: 168mm
Spine width: 14mm