Spatial Sequential Pattern Mining for Seismic Data

• DOI: 10.5753/sbbd.2016.24335
• Publication Date: 2023-05-29T17:29:06Z
• Authors: Riccardo Campisano; Fabio Porto; Esther Pacitti; Florent Masseglia; Eduardo Ogasawara
• Keywords: Sequence (biology); Sequential Pattern Mining

A myriad of applications from different domains collects time series data for further analysis. In many them, such as seismic datasets, the observed is also associated to a space dimension, which corresponds, in fact, spatial-time series. The analysis these datasets difficult due both continuous nature and relationship between spatial dimensions. Meanwhile, sequential patterns mining techniques have been successfully used large volume transactional databases obtain insights data. this work, we start exploring discovery frequent datasets. For that, discretize values into symbols adapt well known algorithm mine dataset. To better understand quality identified patterns, visualize them over original traces images. Our preliminary results indicate that study sequence promising.