Description
ofTutorial

Title :
Mining Attributed Networks

Organizer :

• Rushed Kanawati
• Martin Atzmueller
• Christine Largeron

Abstract :

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 – including methods such as community detection, link prediction or information diffusion. However, the focus has mainly been on simple (monoplex) networks which capture one relation and do not include further attributive information. However, with the growing complexity of heterogeneous data, heterogeneous networks, and in particular attributed 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 attributed networks. This tutorial provides a categorization of attributed networks, generalizing previous approaches, and outlines important principles, methods, tools and future research directions in this emerging field. In particular, we cover the modeling of complex networks, multiplex networks, and various methods on mining attributed networks.