Software Foundations for Data Interoperability and Large Scale Graph Data Analytics: 4th International Workshop, SFDI 2020, and 2nd International Workshop, LSGDA 2020, held in Conjunction with VLDB 2020, Tokyo, Japan, September 4, 2020, Proceedings

Discovering communities that naturally exist as groups of fine-connected users is one the most important tasks for network data analytics and has tremendous real applications. In recent year, community search in attributed graphs has begun to attract attention, which aims to find communities that are both structure and attribute cohesive. Whereas, searching a community that is structure cohesive but attribute diversified, denoted as attribute diversified community search, is still at preliminary stage. In this paper, we introduce our recent effort for discovering attribute diversified community. In fact, for different applications, the needs of attribute diversification for modelling the community are quite different. We introduce three attribute diversified community models in which attribute diversification takes different roles for presenting objective, query requirement, and constraint. We also discuss major techniques for speeding up the attribute diversified community search.