Results 11 to 20 of about 846,106 (226)
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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Finding the True Frequent Itemsets [PDF]
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014 Frequent Itemsets (FIs) mining is a fundamental primitive in data mining. It requires to identify all itemsets appearing in at least a fraction $θ$ of a transactional dataset $\mathcal{D}$. Often though, the ultimate goal of mining $\mathcal{D}$ is not an analysis of the dataset \emph{per se}, but the understanding of the underlying process that ...
Riondato, Matteo, VANDIN, FABIO
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Mining Frequent Itemsets in a Stream [PDF]
Seventh IEEE International Conference on Data Mining (ICDM 2007), 2007 We study the problem of finding frequent itemsets in a continuous stream of transactions. The current frequency of an itemset in a stream is defined as its maximal frequency over all possible windows in the stream from any point in the past until the current state that satisfy a minimal length constraint.
Toon Calders +2 more
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High Scalability Document Clustering Algorithm Based On Top-K Weighted Closed Frequent Itemsets
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2021 Documents clustering based on frequent itemsets can be regarded a new method of documents clustering which is aimed to overcome curse of dimensionality of items produced by documents being clustered.
Gede Aditra Pradnyana, Arif Djunaidy
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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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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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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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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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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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