Metric and algorithm for similarity between two temporal event sequences calculation

Authors

  • Sergii Nikolaiev Educational and Scientific Complex "Institute for Applied System Analysis" of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine https://orcid.org/0000-0002-2025-8469

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2017.3.12

Keywords:

time stamped quasi periodic events, temporal event sequences similarity metric, computing distance between two real arrays of different length, accuracy, recall, precision for temporal event sequences, algorithm for distance of two event flows estimation

Abstract

In several data analysis applications on temporal events flows, the problem of measuring "similarity" of these sequences arises. There are many different definitions of event sequences but in this paper under the term "sequence of events" the ordered array of the event occurrence times will be understood. In this paper the metric and procedure for similarity calculation between two ordered event sequences is presented. The procedure as the output returns measure of two event flows similarity and set of corresponding indices pairs which represent the mapping of the events between the input sequences.

Author Biography

Sergii Nikolaiev, Educational and Scientific Complex "Institute for Applied System Analysis" of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv

Sergii Sergiiovych Nikolaiev,

a Ph.D. student at Educational and Scientific Complex "Institute for Applied System Analysis" of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine.

Research areas: artificial intelligence, machine and deep learning, obtaining biosignals from video, video processing.

References

Pollock Gary. Holistic trajectories: a study of combined employment, housing and family careers by using multiple-sequence analysis. Journal of the Royal Statistical Society, Series A (Statistics in Society), 170(1): P. 167–183, 2007.

Mannila H., Moen P. Similarity between event types in sequences, Proc. First Intl. Conf. on Data Warehousing and Knowledge Discovery (DaWaK’99), Florence, Italy, 1999, P. 271–280.

Moen P., Attribute, Event Sequence, and Event Type Similarity Notions for Data Mining, Ph.D. thesis, Department of Computer Science, University of Helsinki, Finland, 2000.

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Published

2017-09-29

Issue

No. 3 (2017)

Section

Mathematical methods, models, problems and technologies for complex systems research

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