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Broad Learning Through Fusions: An Application on Social Networks

82,48 
82,48 
2025-07-31 82.4800 InStock
Nemokamas pristatymas į paštomatus per 18-22 darbo dienų užsakymams nuo 19,00 

Knygos aprašymas

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.

Informacija

Autorius: Philip S. Yu, Jiawei Zhang,
Leidėjas: Springer Nature Switzerland
Išleidimo metai: 2019
Knygos puslapių skaičius: 436
ISBN-10: 3030125270
ISBN-13: 9783030125271
Formatas: Knyga kietu viršeliu
Kalba: Anglų
Žanras: Maths for computer scientists

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