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http://dx.doi.org/10.7236/JIIBC.2019.19.2.127

Memory Improvement Method for Extraction of Frequent Patterns in DataBase  

Park, In-Kyu (Dept. of Computer Science, Chungwoon University)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.19, no.2, 2019 , pp. 127-133 More about this Journal
Abstract
Since frequent item extraction so far requires searching for patterns and traversal for the FP-Tree, it is more likely to store the mining data in a tree and thus CPU time is required for its searching. In order to overcome these drawbacks, in this paper, we provide each item with its location identification of transaction data without relying on conditional FP-Tree and convert transaction data into 2-dimensional position information look-up table, resulting in the facilitation of time and spatial accessibility. We propose an algorithm that considers the mapping scheme between the location of items and items that guarantees the linear time complexity. Experimental results show that the proposed method can reduce many execution time and memory usage based on the data set obtained from the FIMI repository website.
Keywords
Frequent Itemset Mining; FP-Growth; Minimum Support; Pruning;
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Times Cited By KSCI : 2  (Citation Analysis)
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