Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology

Mining Frequent Parallel Episodes with Selective Participation

Authors
Christian Borgelt, Christian Braune, Kristian Loewe, Rudolf Kruse
Corresponding Author
Christian Borgelt
Available Online June 2015.
DOI
https://doi.org/10.2991/ifsa-eusflat-15.2015.97How to use a DOI?
Keywords
Parallel episode, temporal imprecision, selective participation, frequent pattern mining.
Abstract
We consider the task of finding frequent parallel episodes in parallel point processes, allowing for imprecise synchrony of the events constituting occurrences (temporal imprecision) as well as incomplete occurrences (selective participation). We tackle this problem with frequent pattern mining based on the CoCoNAD methodology, which is designed to take care of temporal imprecision. To cope with selective participation, we form a reduction sequence of items (event types) based on found frequent patterns and guided by pattern overlap. We evaluate the performance of our method on a large number of data sets with injected parallel episodes.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Christian Borgelt
AU  - Christian Braune
AU  - Kristian Loewe
AU  - Rudolf Kruse
PY  - 2015/06
DA  - 2015/06
TI  - Mining Frequent Parallel Episodes with Selective Participation
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 682
EP  - 689
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.97
DO  - https://doi.org/10.2991/ifsa-eusflat-15.2015.97
ID  - Borgelt2015/06
ER  -