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Broad Learning Through Fusions: An Application on Social Networks - Tapa dura

Zhang, Jiawei; Yu, Philip S.

 
9783030125271: Broad Learning Through Fusions: An Application on Social Networks
Tapa dura
ISBN 10: 3030125270 ISBN 13: 9783030125271
Editorial: Springer, 2019

Sinopsis

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.

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Acerca del autor

Jiawei Zhang is Assistant Professor in the Department of Computer Science at Florida State University. In 2017 he founded IFM Lab, a research oriented academic laboratory, providing the latest information on fusion learning and data mining research works and application tools to both academia and industry.
Philip S. Yu is Professor in the Department of Computer Science at the University of Illinois at Chicago and also holds the Wexler Chair in Information and Technology. He was manager of the Software Tools and Techniques group at the IBM Thomas J. Watson Research Center. Dr. Yu has published more than 500 papers in refereed journals and conferences. He holds or has applied for more than 300 US patents. 


De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2019
Idioma
Inglés
ISBN 10 
3030125270
ISBN 13 
9783030125271
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
436
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