Modeling and Mining Feature-Rich Networks

In the field of web mining and web science, as well as data science and data mining there has been a lot of interest in the analysis of (social) networks. With the growing complexity of heterogeneous data, feature-rich networks have emerged as a powerful modeling approach: They capture data and knowledge at different scales from multiple heterogeneous data sources, and allow the mining and analysis from different perspectives. The challenge is to devise novel algorithms and tools for the analysis of such networks. This tutorial provides a unified perspective on feature-rich networks, focusing on different modeling approaches, in particular multiplex and attributed networks. It outlines important principles, methods, tools and future research directions in this emerging field.