We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
In the last decade there has been an explosion of interest in mining time series data. Literally hundreds of papers have introduced new algorithms to index, classify, cluster and s...
Time series analysis is a wide area of knowledge that studies processes in their evolution. The classical research in the area tends to find global laws underlying the behaviour o...
There has been much recent interest in retrieval of time series data. Earlier work has used a fixed similarity metric (e.g., Euclidean distance) to determine the similarity betwee...
Time series stored as feature vectors can be indexed by multidimensional index trees like R-Trees for fast retrieval. Due to the dimensionality curse problem, transformations are ...