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.