The Longest Common Subsequence Distance using a Complexity Factor

Octavian Lucian Hasna, Rodica Potolea

2016

Abstract

In this paper we study the classic longest common subsequence problem and we use the length of the longest common subsequence as a similarity measure between two time series. We propose an original algorithm for computing the approximate length of the LCSS that uses a discretization step, a complexity invariant factor and a dynamic threshold used for skipping the computation.

References

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Paper Citation


in Harvard Style

Hasna O. and Potolea R. (2016). The Longest Common Subsequence Distance using a Complexity Factor . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016) ISBN 978-989-758-203-5, pages 336-343. DOI: 10.5220/0006067603360343


in Bibtex Style

@conference{kdir16,
author={Octavian Lucian Hasna and Rodica Potolea},
title={The Longest Common Subsequence Distance using a Complexity Factor},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)},
year={2016},
pages={336-343},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006067603360343},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)
TI - The Longest Common Subsequence Distance using a Complexity Factor
SN - 978-989-758-203-5
AU - Hasna O.
AU - Potolea R.
PY - 2016
SP - 336
EP - 343
DO - 10.5220/0006067603360343