Quelltext der Seite Efficient k-NN Search of Time Series in Arbitrary Time Intervals

{{Vortrag
|vortragender=Janek Bettinger
|email=janek.bettinger@student.kit.edu
|vortragstyp=Masterarbeit
|betreuer=Jens Willkomm
|termin=Institutsseminar/2018-03-23
|kurzfassung=The k nearest neighbors (k-NN) of a time series are the k closest sequences within a
dataset regarding a distance measure. Often, not the entire time series, but only specific
time intervals are of interest, e.g., to examine phenomena around special events. While
numerous indexing techniques support the k-NN search of time series, none of them
is designed for an efficient interval-based search. This work presents the novel index
structure Time Series Envelopes Index Tree (TSEIT), that significantly speeds up the k-NN
search of time series in arbitrary user-defined time intervals.
}}