"In this paper we propose a micro-clustering strategy for Functional Box-. plot variables defined on multiple streaming time series splitted in non overlapping. windows. It is a two step strategy. In the first step it performs an on-line summa-. rization keeping updated the set of functional data structures, named Functional. Boxplot micro-clusters; in the second step it reveals the final summarization by pro-. cessing, off-line, the Functional Boxplot micro-clusters. Thus a new definition of. micro-cluster based on using the Functional Boxplot as the centroid is proposed.. Moreover a proximity measure which allows to allocate the data to the new defined. micro-clusters is defined. This will allow to get a graphical summarization of the. streaming time series by five functional basic statistics. The obtained synthesis will. be able to keep track of the dynamic evolution of the streams."
A Clustream strategy for Functional Boxplots on multiple streaming time series
BALZANELLA, Antonio;ROMANO, Elvira
2012
Abstract
"In this paper we propose a micro-clustering strategy for Functional Box-. plot variables defined on multiple streaming time series splitted in non overlapping. windows. It is a two step strategy. In the first step it performs an on-line summa-. rization keeping updated the set of functional data structures, named Functional. Boxplot micro-clusters; in the second step it reveals the final summarization by pro-. cessing, off-line, the Functional Boxplot micro-clusters. Thus a new definition of. micro-cluster based on using the Functional Boxplot as the centroid is proposed.. Moreover a proximity measure which allows to allocate the data to the new defined. micro-clusters is defined. This will allow to get a graphical summarization of the. streaming time series by five functional basic statistics. The obtained synthesis will. be able to keep track of the dynamic evolution of the streams."I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.