Mining subgraphs from propagation networks through temporal dynamic analysis

Saeid Hosseini, Hongzhi Yin, Meihui Zhang, Yuval Elovici, Xiaofang Zhou

2018 19th IEEE International Conference on Mobile Data Management (MDM), 66-75, 2018

An alarm is raised due to a defect in a transportation system. Given a graph over which the alarms propagate, we aim to exploit a set of subgraphs with highly correlated nodes (or entities). The edge weight between each pair of entities can be computed using the temporal dynamics of the propagation process. We retrieve the top k edge weights and each group of connected entities can consequently form a tightly coupled subgraph. However, numerous challenges abound. First, the textual contents associated with the alarms of the same type differ during the propagation process. Hence, in the lack of textual data, the temporal information can only be employed to compute the correlation weights. Second, in many scenarios, the same alarm does not propagate. Third, given a pair of entities, the propagation can occur in both directions. Most of the prior work only consider the time-window and assume that the …