More and more data mining algorithms are applied to a large number of long time series issued by many distributed sensors. The consequence of the huge volume of data is that data ...
Raja Chiky, Laurent Decreusefond, Georges Hé...
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
We introduce FuncICA, a new independent component analysis method for pattern discovery in inherently functional data, such as time series data. FuncICA can be considered an analo...
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 ...
Abstract. In this paper, we introduce a new approach for mining regulatory interactions between genes in microarray time series studies. A number of preprocessing steps transform t...
Michael Egmont-Petersen, Wim de Jonge, Arno Siebes