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...
This paper proposes a novel framework for mining regional colocation patterns with respect to sets of continuous variables in spatial datasets. The goal is to identify regions in ...
Christoph F. Eick, Jean-Philippe Nicot, Rachana Pa...
Effective diagnosis of Alzheimer's disease (AD) is of primary importance in biomedical research. Recent studies have demonstrated that neuroimaging parameters are sensitive a...
Jieping Ye, Kewei Chen, Teresa Wu, Jing Li, Zheng ...
How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, biology and medicine. Existing ...
Theproblemof efficiently and accurately locating patterns of interest in massivetimeseries data sets is an important and non-trivial problemin a wide variety of applications, incl...