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.