Many current programmable architectures designed to exploit data parallelism require computation to be structured to operate on sequentially accessed vectors or streams of data. A...
Nuwan Jayasena, Mattan Erez, Jung Ho Ahn, William ...
In many applications that track and analyze spatiotemporal data, movements obey periodic patterns; the objects follow the same routes (approximately) over regular time intervals. ...
Nikos Mamoulis, Huiping Cao, George Kollios, Mario...
Abstract. Discovering interesting patterns in long sequences, and finding confident association rules within them, is a popular area in data mining. Most existing methods define...
The discovery of emerging patterns (EPs) is a descriptive data mining task defined for pre-classified data. It aims at detecting patterns which contrast two classes and has been ...
Annalisa Appice, Michelangelo Ceci, Carlo Malgieri...
The novel Time Series Data Mining (TSDM) framework is applied to analyzing financial time series. The TSDM framework adapts and innovates data mining concepts to analyzing time ser...