Results 21 to 30 of about 9,218 (205)
MAXLEN-FI: AN ALGORITHM FOR MINING MAXIMUM- LENGTH FREQUENT ITEMSETS FAST
Tạp chí Khoa học Đại học Đà Lạt, 2018 Association rule mining, one of the most important and well-researched techniques of data mining. Mining frequent itemsets are one of the most fundamental and most time-consuming problems in association rule mining.
Phan Thành Huấn, Lê Hoài Bắc
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Efficient Mining of Frequent Itemsets Using Only One Dynamic Prefix Tree
IEEE Access, 2020 Frequent itemset mining is a fundamental problem in data mining area because frequent itemsets have been extensively used in reasoning, classifying, clustering, and so on.
Jun-Feng Qu +5 more
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IEEE Access, 2021 One of the most challenging tasks in association rule mining is that when a new incremental database is added to an original database, some existing frequent itemsets may become infrequent itemsets and vice versa.
Wannasiri Thurachon, Worapoj Kreesuradej
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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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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
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Mining All Non-derivable Frequent Itemsets [PDF]
, 2002 3 ...
Calders, T., GOETHALS, Bart
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On differentially private frequent itemset mining [PDF]
Proceedings of the VLDB Endowment, 2012 We consider differentially private frequent itemset mining. We begin by exploring the theoretical difficulty of simultaneously providing good utility and good privacy in this task. While our analysis proves that in general this is very difficult, it leaves a glimmer of hope in that our proof of difficulty relies on the existence of long ...
Chen, Zeng +2 more
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Signature-based Tree for Finding Frequent Itemsets
Journal of Communications Software and Systems, 2023 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.
Mohamed El Hadi Benelhadj +2 more
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Hiding co-occurring frequent itemsets [PDF]
Proceedings of the 2009 EDBT/ICDT Workshops, 2009 Knowledge hiding, hiding rules/patterns that are inferable from published data and attributed sensitive, is extensively studied in the literature in the context of frequent itemsets and association rules mining from transactional data. The research in this thread is focused mainly on developing sophisticated methods that achieve less distortion in data
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An Efficient Spark-Based Hybrid Frequent Itemset Mining Algorithm for Big Data
Data, 2022 Frequent itemset mining (FIM) is a common approach for discovering hidden frequent patterns from transactional databases used in prediction, association rules, classification, etc. Apriori is an FIM elementary algorithm with iterative nature used to find
Mohamed Reda Al-Bana +2 more
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