Spatio-temporal patterns bring knowledge about sequences of events, the location, and the moment they occur. Finding such patterns is a complex task and of great value for different domains. However, not all patterns are frequent across an entire dataset, occurring instead with frequency in restricted space and time. This work formalizes the Mining of Restricted Sequences in Space and Time, without the use of threshold restrictions for time and space. This allows sequences of different lengths, time intervals, and three-dimensional space to present such patterns. It also provides validation with an implementation tested on a real seismic dataset, resulting in a sensitivity analysis and evaluation of resource usage that indicate the validity and feasibility of the solution.<\/p>\n
Implementations of the algorithms are presented in the article Generalized Spatial-Time Sequence Miner<\/em>, original title: Generaliza\u00e7\u00e3o de Minera\u00e7\u00e3o de Sequ\u00eancias Restritas no Espa\u00e7o e no Tempo<\/em>. In: XXXVI SBBD – Brazilian Symposium on Databases, 2021 <doi:10.5753\/sbbd.2021.17891<\/a>>).<\/p>\n Available at CRAN: <\/strong>https:\/\/CRAN.R-project.org\/package=gstsm<\/a><\/p>\n