GSTSM Package: Finding Frequent Sequences in Constrained Space and Time - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2023

GSTSM Package: Finding Frequent Sequences in Constrained Space and Time

Abstract

Spatial time-stamped sequences have information about time and space where events occur. Mining such sequences can bring important insights. However, not all sequences are frequent over an entire dataset. Some are only common in subsets of time and space. This article explains the first tool for mining these sequences in constrained space and time: the GSTSM R package. It allows users to search for spatio-temporal patterns that are not frequent in the entire database, but are dense in restricted time-space intervals. Thus, making it possible to find non-trivial patterns that would not be found using common data mining tools.
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Dates and versions

lirmm-04283772 , version 1 (14-11-2023)

Identifiers

  • HAL Id : lirmm-04283772 , version 1

Cite

Antonio Castro, Heraldo Borges, Cassio Souza, Jorge Rodrigues, Fábio André Machado Porto, et al.. GSTSM Package: Finding Frequent Sequences in Constrained Space and Time. BDA 2023 – 39e Conférence sur la Gestion de Données – Principes, Technologies et Applications, LIRMM, Oct 2023, Montpellier, France. pp.1-4. ⟨lirmm-04283772⟩
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