A Visual and Interactive Data Exploration Method for Large Data Sets and Clustering
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
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Our ability to accumulate large, complex (multivariate) data setshas far exceeded our ability to effectively process them in search ofpatterns, anomalies, and other interesting features. Conventionalmultivariate visualization techniques generally do not scale wellwith respect to the size of the data set. The focus of this paper ison the interactive visualization of large multivariate data sets basedon a number of novel extensions to the parallel coordinates displaytechnique. We develop a multiresolutional view of the data via hierarchicalclustering, and use a variation on parallel coordinates toconvey aggregation information for the resulting clusters. Users canthen navigate the resulting structure until the desired focus regionand level of detail is reached, using our suite of navigational andfiltering tools. We describe the design and implementation of ourhierarchical parallel coordinates system which is based on extendingthe XmdvTool system. Lastly, we show examples of the toolsand techniques applied to large (hundreds of thousands of records)multivariate data sets.