Scalable Maximal Frequent Episode Mining with Desbordante
Episode mining aims to extract subsequences of events that possess certain distinctive properties and constitute facts valuable to the user. Maximal frequent episode mining concentrates on discovery of frequently-appearing subsequences, which are not included into any other larger frequent subsequence. The state-of-the-art for this problem is the MaxFEM algorithm which enumerates possible subsequences, while applying various pruning techniques to accelerate the search. However, this is a computationally-intensive problem: reducing the minimum number of required subsequence occurrences or increasing the length of the subsequence both substantially raise running time, which limits practical...
| Authors | Maxim Ivanov, Matvei Smirnov, Alisa Strazdina et al. |
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| Primary category | cs.DB |
| Published | 3 July 2026 |
| Last updated at source | 3 July 2026 |
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