title:
 
Mining Frequent Parallel Episodes with Selective Participation
publication:
 
eusflat-15
ISBN:
  978-94-62520-77-6
ISSN:
  1951-6851
DOI:
  doi:10.2991/ifsa-eusflat-15.2015.97 (how to use a DOI)
author(s):
 
Christian Borgelt, Christian Braune, Kristian Loewe, Rudolf Kruse
corresponding author:
 
Christian Borgelt
publication date:
 
June 2015
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.
copyright:
 
© The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/
full text: