Discovering Explorative Patterns from Real-World Complex Networks

The ability to discover patterns of networks is fundamental for structural analysis applied to them. Many ubiquitous patterns demonstrated by real-world networks have been discovered, and corresponding tools for finding them also have been developed. Although existing works have greatly improved our understanding on networks, it is still challenging to precisely model and predict their behaviors mainly because their non-trivial structures usually consists of many fold coexisting patterns which cannot be appropriately and totally uncovered by a single tool exclusively designed for pre-defined ones. In this work, we take an effort to address this issue by introducing a parameter-free algorithm aiming to discover such patterns hidden in an explorative network.