Abstract
In this book, we have introduced the current research works on broad learning and its applications on online social networks. This book has covered 4 main parts, where the first 3 parts include 6 main research directions about broad learning based social network mining problems, including (1) network alignment, (2) link prediction, (3) community detection, (4) information diffusion, (5) viral marketing, and (6) network embedding. These problems introduced in this book are all very important for many concrete real-world social network applications and services. A number of state-of-the-art algorithms have been proposed to solve these problems, which are introduced in great detail in this book. Broad learning is a very promising research area, and several potential future development directions about broad learning will be illustrated in the following sections.
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