A TIFF-Tree Based High Utility Itemset Mining Algorithm

Abstract:

Owing to their major contribution to the total transaction's sales profits, increasingly importance has been attached to high utility itemsets mining. This paper has proposed a TIFF-tree based algorithm, which takes two-pass database scan to obtain the transaction utility information, the conditional matrix of potential high utility is adopted, through the row-column operation, the calculation of transaction utility can be simplified. The experiment result analysis shows that as the decreasing of user-defined threshold, the performance of TIFP-Growth algorithm is much better than the two-phase algorithm.

• Periodical: Advanced Materials Research (Volumes 760-762)
• Pages: 1713-1717
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.760-762.1713
• Online since: September 2013
• Authors: Yi Pan, Bo Zhang
• Keywords: Conditional Matrix, Frequent Pattern Mining, High Utility Itemsets

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