A new algorithm for mining frequent patterns in Can Tree

Hoseini, Masome Sadat; Nadimi-Shahraki, Mohammad H.; Neysiani, Behzad Soleimani

doi:10.1109/kbei.2015.7436153

Cited by 8 publications

(6 citation statements)

References 9 publications

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“…In this section, some basic definitions about frequent pattern mining [10,11], the original Eclat algorithm, and structure of the tissue-like P system with active membranes are introduced.…”

Section: Preliminariesmentioning

confidence: 99%

“…Data mining is a knowledge discovery process from large amounts of data and has been extensively studied in many fields. Frequent pattern mining is a fundamental field of data mining, and the goal is to find patterns that appear frequently in a database [8][9][10][11]. Many algorithms for mining frequent patterns, such as Apriori, FP-growth, and Eclat, to mention only a few, have been developed.…”

Section: Introductionmentioning

confidence: 99%

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An Improved Eclat Algorithm Based on Tissue-Like P System with Active Membranes

2019

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The Eclat algorithm is a typical frequent pattern mining algorithm using vertical data. This study proposes an improved Eclat algorithm called ETPAM, based on the tissue-like P system with active membranes. The active membranes are used to run evolution rules, i.e., object rewriting rules, in parallel. Moreover, ETPAM utilizes subsume indices and an early pruning strategy to reduce the number of frequent pattern candidates and subsumes. The time complexity of ETPAM is decreased from O(t2) to O(t) as compared with the original Eclat algorithm through the parallelism of the P system. The experimental results using two databases indicate that ETPAM performs very well in mining frequent patterns, and the experimental results using four databases prove that ETPAM is computationally very efficient as compared with three other existing frequent pattern mining algorithms.

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Section: Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Improved Eclat Algorithm Based on Tissue-Like P System with Active Membranes

2019

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“…Can-Mining (Hoseini et al 2015) is an algorithm that mines frequent itemsets from a Canonical-Order Tree (Can-Tree) in an incremental manner. Similar to the FP-Growth algorithm, a header table that contains information of all the database items is used in the algorithm.…”

Section: Can-mining Algorithmmentioning

confidence: 99%

“…10 Architecture of the Can-mining algorithm. Reproduced with permission from (Hoseini et al 2015) in Fig. 11.…”

Section: Extract Algorithmmentioning

confidence: 99%

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Algorithms for frequent itemset mining: a literature review

Chee¹,

Jaafar²,

Aziz³

et al. 2018

Artif Intell Rev

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Data Analytics plays an important role in the decision making process. Insights from such pattern analysis offer vast benefits, including increased revenue, cost cutting, and improved competitive advantage. However, the hidden patterns of the frequent itemsets become more time consuming to be mined when the amount of data increases over the time. Moreover, significant memory consumption is needed in mining the hidden patterns of the frequent itemsets due to a heavy computation by the algorithm. Therefore, an efficient algorithm is required to mine the hidden patterns of the frequent itemsets within a shorter run time and with less memory consumption while the volume of data increases over the time period. This paper reviews and presents a comparison of different algorithms for Frequent Pattern Mining (FPM) so that a more efficient FPM algorithm can be developed.

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An integrated cuckoo search-genetic algorithm for mining frequent itemsets

Sukanya

Thangaiah

2022

Journal of Discrete Mathematical Sciences and Cryptography

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A new algorithm for mining frequent patterns in Can Tree

Cited by 8 publications

References 9 publications

An Improved Eclat Algorithm Based on Tissue-Like P System with Active Membranes

An Improved Eclat Algorithm Based on Tissue-Like P System with Active Membranes

Algorithms for frequent itemset mining: a literature review

An integrated cuckoo search-genetic algorithm for mining frequent itemsets

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