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An algebraic semigroup method for discovering maximal frequent itemsets
Open Mathematics, 2022 Discovering maximal frequent itemsets is an important issue and key technique in many data mining problems such as association rule mining. In the literature, generating maximal frequent itemsets proves either to be NP-hard or to have O(l34l(m+n))O\left({
Liu Jiang +5 more
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Finding the True Frequent Itemsets [PDF]
, 2013 Frequent Itemsets (FIs) mining is a fundamental primitive in data mining. It requires to identify all itemsets appearing in at least a fraction $\theta$ of a transactional dataset $\mathcal{D}$.
Riondato, Matteo, Vandin, Fabio
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Hiding Sensitive Frequent Itemsets over Privacy Preserving Distributed Data [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2013 Data mining is the process of extracting hidden patterns from data. One of the most important activities in data mining is the association rule mining and the new head for data mining research area is privacy of mining.
Alaa Jumaa, Sufyan Al-Janabi, Nazar Ali
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A review on big data based parallel and distributed approaches of pattern mining
Journal of King Saud University: Computer and Information Sciences, 2022 Pattern mining is a fundamental technique of data mining to discover interesting correlations in the data set. There are several variations of pattern mining, such as frequent itemset mining, sequence mining, and high utility itemset mining. High utility
Sunil Kumar, Krishna Kumar Mohbey
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Parallel Algorithm for Frequent Itemset Mining on Intel Many-core Systems [PDF]
, 2018 Frequent itemset mining leads to the discovery of associations and correlations among items in large transactional databases. Apriori is a classical frequent itemset mining algorithm, which employs iterative passes over database combining with generation
Zymbler, Mikhail
core +3 more sources
Finding Stable Periodic-Frequent Itemsets in Big Columnar Databases
IEEE Access, 2023 Stable periodic-frequent itemset mining is essential in big data analytics with many real-world applications. It involves extracting all itemsets exhibiting stable periodic behaviors in a temporal database.
Hong N. Dao +5 more
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A GENERAL SURVEY ON FREQUENT PATTERN MINING USING GENETIC ALGORITHM [PDF]
ICTACT Journal on Soft Computing, 2012 In recent years, data mining is an important aspect for generating association rules among the large number of itemsets. Association rule mining is one of the techniques in data mining that that has two sub processes. First, the process called as finding
K. Poornamala, R. Lawrance
doaj
CPU Parallelization Eclat Algorithm Based on Bit Storage Tid [PDF]
Jisuanji gongcheng, 2018 The Eclat algorithm uses vertical data representation and does not require complex data structures.However,the intersection count generation mode causes a large amount of memory consumption and low mining efficiency in the process of mining frequent ...
SUN Zongxin,ZHANG Guiyun
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Right-Hand Side Expanding Algorithm for Maximal Frequent Itemset Mining
Applied Sciences, 2021 When it comes to association rule mining, all frequent itemsets are first found, and then the confidence level of association rules is calculated through the support degree of frequent itemsets.
Yalong Zhang +4 more
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Video Mining with Frequent Itemset Configurations [PDF]
, 2006 We present a method for mining frequently occurring objects and scenes from videos. Object candidates are detected by finding recurring spatial arrangements of affine covariant regions. Our mining method is based on the class of frequent itemset mining algorithms, which have proven their efficiency in other domains, but have not been applied to video ...
Quack, Till +2 more
openaire +2 more sources