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

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Provided by: Springer Healthcare
Topic: Big Data
Format: PDF
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, the authors 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 their proposed algorithm.
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