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Broad Learning Through Fusions

Broad Learning Through Fusions An Application on Social Networks

Paperback (14 Aug 2020)

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Publisher's Synopsis

This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.

Book information

ISBN: 9783030125301
Publisher: Springer International Publishing
Imprint: Springer
Pub date:
Language: English
Number of pages: 419
Weight: 753g
Height: 254mm
Width: 178mm
Spine width: 23mm