Discovering Frequent Closed Embedded Sub-DAGs in Spatio-Temporal Event Data
We propose a novel approach to mine patterns in spatio-temporal event data based on discovering frequent closed embedded sub-Directed Acyclic Graphs (DAGs). In our method, event instances are represented as nodes labelled by event types, while edges capture spatio-temporal following relationships. We formally define the considered class of patterns and provide the rationale for focusing on closed sub-DAGs as compact and non-redundant representations of recurring interaction patterns. We implement the DigDag algorithm for mining such patterns and experimentally compare its efficiency with two related approaches: propagation pattern mining using the SLEUTH algorithm and Cascading Spatio-Tem...
| Authors | Piotr S. Maciąg |
|---|---|
| Primary category | cs.DB |
| Published | 7 July 2026 |
| Last updated at source | 7 July 2026 |
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