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UBC CS TR-2005-25 Summary

Visual Mining of Power Sets with Large Alphabets, December 25, 2005 Tamara Munzner, Qiang Kong, Raymond T. Ng, Jordan Lee, Janek Klawe, Dragana Radulovic and Carson K. Leung, 10 pages

We present the PowerSetViewer visualization system for the lattice-based mining of power sets. Searching for itemsets within the power set of a universe occurs in many large dataset knowledge discovery contexts. Using a spatial layout based on a power set provides a unified visual framework at three different levels: data mining on the filtered dataset, browsing the entire dataset, and comparing multiple datasets sharing the same alphabet. The features of our system allow users to find appropriate parameter settings for data mining algorithms through lightweight visual experimentation showing partial results. We use dynamic constrained frequent set mining as a concrete case study to showcase the utility of the system. The key challenge for spatial layouts based on power set structure is handling large alphabets, because the size of the power set grows exponentially with the size of the alphabet. We present scalable algorithms for enumerating and displaying datasets containing between 1.5 and 7 million itemsets, and alphabet sizes of over 40,000.


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