Mining Frequent Synchronous Patterns with a Graded Notion of Synchrony

DOI

10.2991/ifsa-eusflat-15.2015.189How to use a DOI?

Keywords

Graded synchrony, synchronous events, frequent pattern, pattern mining.

Abstract

We present methods to find (significant) frequent synchronous patterns in event sequences, 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 constituting events. Since transferring earlier work (using a binary notion of synchrony) poses certain problems, we opt for an efficient approximation scheme to compute the pattern support. Furthermore, we transfer methods for filtering for significant and removing induced patterns, which require adaptations. Finally, we demonstrate the effectiveness of our approach with experiments on a large number of data sets with injected synchronous patterns.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Salatiel Ezennaya-Gomez
AU  - Christian Borgelt
PY  - 2015/06
DA  - 2015/06
TI  - Mining Frequent Synchronous Patterns with a Graded Notion of Synchrony
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  - 1338
EP  - 1345
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.189
DO  - 10.2991/ifsa-eusflat-15.2015.189
ID  - Ezennaya-Gomez2015/06
ER  -