Fuzzy Longest Common Subsequence Matching With FCM Using R
Artificial Intelligence
2016-12-20 v2
Abstract
Capturing the interdependencies between real valued time series can be achieved by finding common similar patterns. The abstraction of time series makes the process of finding similarities closer to the way as humans do. Therefore, the abstraction by means of a symbolic levels and finding the common patterns attracts researchers. One particular algorithm, Longest Common Subsequence, has been used successfully as a similarity measure between two sequences including real valued time series. In this paper, we propose Fuzzy Longest Common Subsequence matching for time series.
Keywords
Cite
@article{arxiv.1508.03671,
title = {Fuzzy Longest Common Subsequence Matching With FCM Using R},
author = {Ibrahim Ozkan and I. Burhan Turksen},
journal= {arXiv preprint arXiv:1508.03671},
year = {2016}
}
Comments
Prepared April 17, 2013. 26 Pages, updated March 10, 2016 included R code