Interactive visual exploration of neighbor-based patterns in data streams

Authors:
Di Yang;Zhenyu Guo;Zaixian Xie;Elke A. Rundensteiner;Matthew O. Ward
Affiliations:
Worcester Polytechnic Institute, Worcester, MA, USA;Worcester Polytechnic Institute, Worcester, MA, USA;Worcester Polytechnic Institute, Worcester, MA, USA;Worcester Polytechnic Institute, Worcester, MA, USA;Worcester Polytechnic Institute, Worcester, MA, USA
Venue:
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Year:
2010

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Abstract

We will demonstrate our system, called V iStream, supporting interactive visual exploration of neighbor-based patterns [7] in data streams. V iStream does not only apply innovative multi-query strategies to compute a broad range of popular patterns, such as clusters and outliers, in a highly efficient manner, but it also provides a rich set of visual interfaces and interactions to enable real-time pattern exploration. With ViStream, analysts can easily interact with pattern mining processes by navigating along the time horizons, abstraction levels and parameter spaces, and thus better understand the phenomena of interest.