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A Tree-Based Approach for Frequent Pattern Mining from Uncertain Data

Carson Kai-Sang LeungContact Information, Mark Anthony F. MateoContact Information and Dale A. BrajczukContact Information

(1)  The University of Manitoba, Winnipeg, MB, Canada
Abstract
Many frequent pattern mining algorithms find patterns from traditional transaction databases, in which the content of each transaction—namely, items—is definitely known and precise. However, there are many real-life situations in which the content of transactions is uncertain. To deal with these situations, we propose a tree-based mining algorithm to efficiently find frequent patterns from uncertain data, where each item in the transactions is associated with an existential probability. Experimental results show the efficiency of our proposed algorithm.

Contact Information Carson Kai-Sang Leung
Email: kleung@cs.umanitoba.ca

Contact Information Mark Anthony F. Mateo
Email: mfmateo@cs.umanitoba.ca

Contact Information Dale A. Brajczuk
Email: umbrajcz@cs.umanitoba.ca
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