We describe a domain-independent, unsupervised algorithm for refined segmentation of time series data into meaningful episodes, focusing on the problem of text segmentation. The V...
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
The last decade has witnessed a tremendous growths of interests in applications that deal with querying and mining of time series data. Numerous representation methods for dimensi...
Hui Ding, Goce Trajcevski, Peter Scheuermann, Xiao...
Abstract. Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the ...
: Temporal data mining is concerned with the analysis of temporal data and finding temporal patterns, regularities, trends, clusters in sets of temporal data. Wavelet transform pro...