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Discovering Robustly Connected Subgraphs with Simple Descriptions


We study the problem of discovering robustly connected subgraphs that have simple descriptions. Our aim is, hence, to discover vertex sets which not only a) induce a subgraph that is difficult to fragment into disconnected components, but also b) can be selected from the entire graph using just a simple conjunctive query on their vertex attributes. Since many subgraphs do not have such a simple logical description, first mining robust subgraphs and post-hoc discovering their description leads to sub-optimal results. Instead, we propose to optimise over describable subgraphs only. To do so efficiently we propose a non-redundant iterative deepening approach, which we equip with a linear-time tight optimistic estimator that allows pruning large parts of the search space. Extensive empirical evaluation shows that our method can handle large real-world graphs, and discovers easily interpretable and meaningful subgraphs.

Conference / Medium

IEEE International Conference on Data Mining (ICDM)

Date published


Date last modified

2021-05-10 11:34:02