A Comparative Study on Similarity Analysis in Time Series Data Mining
Time series is a sequence of values observed over the
time. There are several patterns such as periodic patterns, similarity
patterns, seasonal patterns, etc. This paper deals with the similarity
analysis, which is concerned with efficiently locating subsequences in
large archives of sequences. It also discusses the appropriate use of
Piecewise Constant Approximation (PCA) and coefficient of variation
method for data reduction technique. Finally, the fuzzy c-means and
k-medoid cluster analysis are applied to the reduced data to measure
the similarity between two sequences and the results are compared
numerically and graphically.
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