Data streams are one of the most relevant new data sources, they refer to flows of data that come at a very high rate. Let us consider a stock-exchange market, where n different stocks with p considered attributes (e.g. price, quantity, seller/buyer id, . . .) are negotiated all day long. The distinguishing feature in data streams analysis is that the focus is on transient relations. The present paper proposes a visualization tool exploiting Multidimensional Data Analisis (MDA) techniques to represent the evolving association structures among attributes over different time-frames. The general aim is to detect the stability of the deviation from indipendence in the occurrence of an observed set of attributes stored as binary stream.
Titolo: | Binary data flow visualization onfactorial axes |
Autori: | |
Data di pubblicazione: | 2007 |
Rivista: | |
Abstract: | Data streams are one of the most relevant new data sources, they refer to flows of data that come at a very high rate. Let us consider a stock-exchange market, where n different stocks with p considered attributes (e.g. price, quantity, seller/buyer id, . . .) are negotiated all day long. The distinguishing feature in data streams analysis is that the focus is on transient relations. The present paper proposes a visualization tool exploiting Multidimensional Data Analisis (MDA) techniques to represent the evolving association structures among attributes over different time-frames. The general aim is to detect the stability of the deviation from indipendence in the occurrence of an observed set of attributes stored as binary stream. |
Handle: | http://hdl.handle.net/11580/19656 |
Appare nelle tipologie: | 1.1 Articolo in rivista |
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