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Landmarks: a New Model for Similarity-based Pattern Querying in Time Series Databases.
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||Nov 30, 1999. 00:00:00
The problem of finding similar time sequences has vexed us for quite a while.
The central issue is that similarity lies in the eye of the beholder -- any
formal definition of similarity is likely to be suitable only for certain very
specific contexts. For the most part, the approach taken by various authors has
been to permit "transformations" (from some allowed class, such as scaling,
shifting, time-warping, and so on), and then performing a distance measurement.
While a rich enough class of transformations can accomplish a great deal,
permitting a large class of transformations means that an expensive search is
required to find the sequence of transformations that minimizes the distance between
two given time series.
I like this paper because it proposes a nice appealing definition of a landmark,
and proposes a notion of landmark similarity that is very easy to work with
in terms of tractability, yet can do a decent job of capturing similarity in
(Review from Digital Review)