Interactive visual exploration of neighbor-based patterns in data streams
Author(s) -
Di Yang,
Zhenyu Guo,
Zaixian Xie,
Elke A. Rundensteiner,
Matthew O. Ward
Publication year - 2010
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/1807167.1807305
Subject(s) - computer science , interactive visual analysis , abstraction , outlier , data stream mining , set (abstract data type) , range (aeronautics) , visual analytics , data mining , visualization , streams , data exploration , theoretical computer science , artificial intelligence , philosophy , materials science , epistemology , composite material , programming language , computer network
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.
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