2018/04/26 by Anton Kocheturov, Petar Momčilović, Kocheturov, Anton +5
Computer Science · #Data Management and Algorithms #Data Mining Algorithms and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Time Series Analysis and Forecasting
paper · pdf · doi:10.48550/arxiv.1804.10025
openalex publication_date 2018/04/26 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
Temporal Pattern Mining (TPM) is the problem of mining predictive complex\ntemporal patterns from multivariate time series in a supervised setting. We\ndevelop a new method called the Fast Temporal Pattern Mining with Extended\nVertical Lists. This method utilizes an extension of the Apriori property which\nrequires a more complex pattern to appear within records only at places where\nall of its subpatterns are detected as well. The approach is based on a novel\ndata structure called the Extended Vertical List that tracks positions of the\nfirst state of the pattern inside records. Extensive computational results\nindicate that the new method performs significantly faster than the previous\nversion of the algorithm for TMP. However, the speed-up comes at the expense of\nmemory usage.\n