Izvorni znanstveni članak
https://doi.org/10.24138/jcomss-2022-0065
Signature-based Tree for Finding Frequent Itemsets
Mohamed El Hadi Benelhadj
; Faculty of Science and Technologies, Tamanrasset University, Algeria
Mohamed Mahmoud Deye
; Cheikh Anta Diop University of Dakar, Senegal
Yahya Slimani
; Institute of Multimedia Art of Manouba (ISAMM), University of Manouba, Tunisia
Sažetak
The efficiency of a data mining process depends on the data structure used to find frequent itemsets. Two approaches are possible: use the original transaction dataset or transform it into another more compact structure. Many algorithms use trees as compact structure, like FP-Tree and the associated algorithm FP-Growth. Although this structure reduces the number of scans (only 2), its efficiency depends on two criteria: (i) the size of the support (small or large); (ii) the type of transaction dataset (sparse or dense). But these two criteria can generate very large trees. In this paper, we propose a new tree-based structure that emphasizes on transactions and not on itemsets. Hence, we avoid the problem of support values that have a negative impact on the generated tree.
Ključne riječi
Data Mining; Data compression; Data storage; Tree structure; Signature
Hrčak ID:
299773
URI
Datum izdavanja:
31.3.2023.
Posjeta: 217 *