Efficiently mining gapped and window constraint frequent sequential patterns

Hugo Alatrista-Salas, Agustin Guevara-Cogorno, Yoshitomi Maehara, Miguel Nunez-del-Prado

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


Sequential pattern mining is one of the most widespread data mining tasks with several real-life decision-making applications. In this mining process, constraints were added to improve the mining efficiency for discovering patterns meeting specific user requirements. Therefore, the temporal constraints, in particular, those that arise from the implicit temporality of sequential patterns, will have the ability to efficiently apply temporary restrictions such as, window and gap constraints. In this paper, we propose a novel window and gap constrained algorithms based on the well-known PrefixSpan algorithm. For this purpose, we introduce the virtual multiplication operation aiming for a generalized window mining algorithm that preserves other constraints. We also extend the PrefixSpan Pseudo-Projection algorithm to mining patterns under the gap-constraint. Our performance study shows that these extensions have the same time complexity as PrefixSpan and good linear scalability.

Original languageEnglish
Title of host publicationModeling Decisions for Artificial Intelligence - 17th International Conference, MDAI 2020, Proceedings
EditorsVicenc Torra, Yasuo Narukawa, Jordi Nin, Núria Agell
Number of pages12
ISBN (Print)9783030575236
StatePublished - 2020
Externally publishedYes
Event17th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2020 - Sant Cugat del Vallès, Spain
Duration: 2 Sep 20204 Sep 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12256 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2020
CitySant Cugat del Vallès


  • Gap constraint
  • Sequential pattern mining
  • Temporal constraints
  • Window constraint


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