MaDGM: Multi-aspect Dynamic Graph Miner

Dynamic graphs model time-varying interactions between related entities in a network. Extensive studies have been carried out on the mining of frequent, regular, and periodic behavior of such interactions. Some of the previous research focused on providing users the platform to mine periodic patterns on a single aspect (structure, weight, or direction) at a time. However, the designed tool needs to be run multiple times, to mine significant information that is gained by the study of multiple aspects simultaneously in a network. Moreover, it lacks capability of mining the regular patterns in a network, and the applicability of which lies in wide-ranging domains. In the present research, a tool, the Multi-aspect Dynamic Graph Miner, is proposed that fills up these gaps by providing users an integrated platform for mining regular and periodic patterns on multiple aspects. Besides the primary features, it facilitates easy visualization of tool output and provides a converter for the users of previous works that some portion of our software is based on. We further discuss its applicability by testing on real-world and synthetic datasets.