Interactive Temporal Association Analytics - Qin, Xiao;Ashan, Ramoza;Rundensteiner, Elke
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Nowadays batches of data are continuously transmitted from a rich variety of sources including websites, mobile devices and other data sources, henceforth referred to as evolving datasets. Discovering associations and their dynamics hidden in such large evolving datasets has been recognized as critical for domains ranging from market products analysis, stock trend monitoring, targeted advertising to weather forecasting.

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Produktbeschreibung
Nowadays batches of data are continuously transmitted from a rich variety of sources including websites, mobile devices and other data sources, henceforth referred to as evolving datasets. Discovering associations and their dynamics hidden in such large evolving datasets has been recognized as critical for domains ranging from market products analysis, stock trend monitoring, targeted advertising to weather forecasting.
Autorenporträt
Xiao Qin is a Ph.D. candidate in the Computer Science Department at Worcester Polytechnic Institute and an ORISE fellow with U.S. Food and Drug Administration. His general research interests include data mining, big data analytics and information management.