Times Series vs. Stream Mining
Time Series analysis는 이미 시간 순으로 기록된 전체 데이터 셋을 가지고 유의미한 정보를 추출한다. 반면에 Stream Mining는 전체 데이터 셋을 알 수 없는 상황에서 실시간으로 들어오는 stream data들을 처리하여 유의미한 정보를 추출한다.
In time series analysis, dynamic time warping (DTW) is one of the algorithms for measuring similarity between two temporal sequences, which may vary in speed. DTW has been applied to temporal sequences of video, audio, and graphics data
Clearly these two series follow the same pattern, but the blue curve is longer than the red. If we apply the one-to-one match, shown in the top, the mapping is not perfectly synced up and the tail of the blue curve is being left out.
DTW overcomes the issue by developing a one-to-many match so that the troughs and peaks with the same pattern are perfectly matched, and there is no left out for both curves(shown in the bottom top).
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