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Authors: Salatiel Ezennaya-Gomez 1 and Christian Borgelt 2

Affiliations: 1 European Centre for Soft Computing and Otto-von-Guericke University, Spain ; 2 European Center for Soft Computing, Spain

Keyword(s): Graded Synchrony, Synchronous Events, Temporal Imprecision, Selective Participation, Frequent Pattern Mining.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: We consider the task of finding frequent parallel episodes in parallel point processes (or event sequences), allowing for imprecise synchrony of the events constituting occurrences (temporal imprecision) as well as incomplete occurrences (selective participation). The temporal imprecision problem is tackled by frequent pattern mining using a graded notion of synchrony that captures both the number of instances of a pattern as well as the precision of synchrony of its events. To cope with selective participation, a reduction sequence of items (or event types) is formed based on found frequent patterns and guided by pattern overlap. We evaluate the performance of this method on a large number of data sets with injected parallel episodes. We demonstrate that, in contrast to binary synchrony where it pays to consider the pattern instances, graded synchrony performs better with a pattern-based scheme than with an instance-based one, thus simplifying the procedure.

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Paper citation in several formats:
Ezennaya-Gomez, S. and Borgelt, C. (2015). Mining Significant Frequent Patterns in Parallel Episodes with a Graded Notion of Synchrony and Selective Participation. In Proceedings of the 7th International Joint Conference on Computational Intelligence (ECTA 2015) - NCTA; ISBN 978-989-758-157-1, SciTePress, pages 39-48. DOI: 10.5220/0005600600390048

@conference{ncta15,
author={Salatiel Ezennaya{-}Gomez. and Christian Borgelt.},
title={Mining Significant Frequent Patterns in Parallel Episodes with a Graded Notion of Synchrony and Selective Participation},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence (ECTA 2015) - NCTA},
year={2015},
pages={39-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005600600390048},
isbn={978-989-758-157-1},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Computational Intelligence (ECTA 2015) - NCTA
TI - Mining Significant Frequent Patterns in Parallel Episodes with a Graded Notion of Synchrony and Selective Participation
SN - 978-989-758-157-1
AU - Ezennaya-Gomez, S.
AU - Borgelt, C.
PY - 2015
SP - 39
EP - 48
DO - 10.5220/0005600600390048
PB - SciTePress