Results 11 to 20 of about 9,424 (197)
Multi-Objective Optimization for High-Dimensional Maximal Frequent Itemset Mining
Applied Sciences, 2021 The solution space of a frequent itemset generally presents exponential explosive growth because of the high-dimensional attributes of big data. However, the premise of the big data association rule analysis is to mine the frequent itemset in high ...
Yalong Zhang +4 more
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Parallel Mining Algorithm of Frequent Itemset Based on N-list and DiffNodeset Structure [PDF]
Jisuanji kexue, 2023 Frequent itemset mining is a basic problem of data mining and plays an important role in many data mining applications.In order to solve the problems of the parallel frequent itemset mining algorithm(MrPrePost) in big data environment,such as algorithm ...
ZHANG Yang, WANG Rui, WU Guanfeng, LIU Hongyi
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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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An Incremental Interesting Maximal Frequent Itemset Mining Based on FP-Growth Algorithm
Complexity, 2022 Frequent itemset mining is the most important step of association rule mining. It plays a very important role in incremental data environments. The massive volume of data creates an imminent need to design incremental algorithms for the maximal frequent ...
Hussein A. Alsaeedi, Ahmed S. Alhegami
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Proposed Algorithm for Extracting Association Rule Depend on Closed Frequent Itemset (EACFI) [PDF]
Engineering and Technology Journal, 2011 Association rules are important one of data mining activities. All algorithms of association rule mining consist of finding frequency of itemsets, which satisfy a minimum support threshold, and then compute confidence percentage for each k-itemsets to ...
Emad k. Jbbar, Yaser Munther
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Top ‘N’ Variant Random Forest Model for High Utility Itemsets Recommendation [PDF]
EAI Endorsed Transactions on Energy Web, 2021 High-utility based itemset mining is the advancement of recurrent pattern mining that discovers occurrence of frequent transactions from a huge database.
Pazhaniraja N +3 more
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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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Knowledge Engineering and Data Science, 2020 Apriori algorithm is one of the methods with regard to association rules in data mining. This algorithm uses knowledge from an itemset previously formed with frequent occurrence frequencies to form the next itemset.
Adie Wahyudi Oktavia Gama +1 more
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Majalah Ilmiah Teknologi Elektro, 2018 Algoritma FP-growth adalah algoritma data mining yang digunakan untuk menemukan frequent itemset pada data keranjang belanja. Frequent itemset adalah kelompok barang yang sering dibeli bersamaan dalam satu keranjang belanja. Analisa frequent itemset akan
I Gusti Agung Indrawan +2 more
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On the Complexity of Mining Itemsets from the Crowd Using Taxonomies [PDF]
, 2013 We study the problem of frequent itemset mining in domains where data is not recorded in a conventional database but only exists in human knowledge. We provide examples of such scenarios, and present a crowdsourcing model for them.
Amarilli, Antoine +2 more
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