CTU-Mine: An Efficient High Utility Itemset Mining Algorithm Using the Pattern Growth Approach

High utility sequential pattern mining is a popular topic in data mining with the main purpose is to extract sequential patterns with high utility in the sequence database. Many recent works have proposed methods to solve this problem. However, most of them does not consider item intervals of sequential patterns which can lead to the extraction of sequential patterns with too long item interval, thus making little sense. In this paper, we propose a High Utility Item Interval Sequential Pattern (HUISP) algorithm to solve this problem. Our algorithm uses pattern growth approach and some techniques to increase algorithm's performance.

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HIGH UTILITY ITEM INTERVAL SEQUENTIAL PATTERN MINING ALGORITHM

Journal of Computer Science and Cybernetics ◽

10.15625/1813-9663/36/1/14398 ◽

2020 ◽

Vol 36 (1) ◽

pp. 1-15

Author(s):

Tran Huy Duong ◽

Nguyen Truong Thang ◽

Vu Duc Thi ◽

Tran The Anh

Keyword(s):

Data Mining ◽

Pattern Mining ◽

Sequential Pattern Mining ◽

Sequential Pattern ◽

Sequential Patterns ◽

Sequence Database ◽

Mining Algorithm ◽

Pattern Growth ◽

High Utility ◽

Growth Approach

High utility sequential pattern mining is a popular topic in data mining with the main purpose is to extract sequential patterns with high utility in the sequence database. Many recent works have proposed methods to solve this problem. However, most of them does not consider item intervals of sequential patterns which can lead to the extraction of sequential patterns with too long item interval, thus making little sense. In this paper, we propose a High Utility Item Interval Sequential Pattern (HUISP) algorithm to solve this problem. Our algorithm uses pattern growth approach and some techniques to increase algorithm's performance.

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A high utility itemset mining algorithm based on subsume index

Knowledge and Information Systems ◽

10.1007/s10115-015-0900-1 ◽

2015 ◽

Vol 49 (1) ◽

pp. 315-340 ◽

Cited By ~ 8

Author(s):

Wei Song ◽

Zihan Zhang ◽

Jinhong Li

Keyword(s):

Itemset Mining ◽

Mining Algorithm ◽

High Utility

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A TIFF-Tree Based High Utility Itemset Mining Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.760-762.1713 ◽

2013 ◽

Vol 760-762 ◽

pp. 1713-1717

Author(s):

Yi Pan ◽

Bo Zhang

Keyword(s):

Two Phase ◽

Column Operation ◽

Itemset Mining ◽

Mining Algorithm ◽

Utility Information ◽

High Utility ◽

High Utility Itemsets ◽

Result Analysis ◽

Better Than

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.

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