Results 11 to 20 of about 2,597 (181)
arules - A Computational Environment for Mining Association Rules and Frequent Item Sets [PDF]
Journal of Statistical Software, 2005 Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases.
Michael Hahsler +2 more
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Theoretical Properties of Closed Frequent Itemsets in Frequent Pattern Mining
MathematicsClosed frequent itemsets (CFIs) play a crucial role in frequent pattern mining by providing a compact and complete representation of all frequent itemsets (FIs).
Huina Zhang +4 more
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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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Condensed representation of frequent itemsets [PDF]
Proceedings of the 18th International Database Engineering & Applications Symposium on - IDEAS '14, 2014 One of the major problems in pattern mining is still the problem of pattern explosion, i.e., the large amounts of patterns produced by the mining algorithms when analyzing a database with a predefined minimum support threshold. The approach we take to overcome this problem aims for automatically inferring variables from the patterns found, in order to ...
Daniel Serrano, Cláudia Antunes
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DISCOVERING CONFUSING FREQUENT ITEMSETS
Tạp chí Khoa học Đại học Đà Lạt, 2018 Frequent itemset mining is one of the most important research areas in the field of association rule mining. Exploiting frequent itemsets at different abstraction levels of data will yield valuable knowledge.
Huỳnh Thành Lộc
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Concept Lattice Method for Spatial Association Discovery in the Urban Service Industry
ISPRS International Journal of Geo-Information, 2020 A relative lag in research methods, technical means and research paradigms has restricted the rapid development of geography and urban computing. Hence, there is a certain gap between urban data and industry applications.
Weihua Liao, Zhiheng Zhang, Weiguo Jiang
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Axiomatization of frequent itemsets
Theoretical Computer Science, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Calders, Toon, Paredaens, J.
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Efficiently Mining Frequent Itemsets on Massive Data
IEEE Access, 2019 Frequent itemset mining is an important operation to return all itemsets in the transaction table, which occur as a subset of at least a specified fraction of the transactions.
Xixian Han +5 more
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A Parallel Apriori Algorithm and FP- Growth Based on SPARK [PDF]
ITM Web of Conferences, 2021 Frequent Itemset Mining is an important data mining task in real-world applications. Distributed parallel Apriori and FP-Growth algorithm is the most important algorithm that works on data mining for finding the frequent itemsets.
Gupta Priyanka, Sawant Vinaya
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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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