Results 11 to 20 of about 739 (208)
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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Discovering Frequent Closed Itemsets for Association Rules [PDF]
, 1999 In this paper, we address the problem of finding frequent itemsets in a database. Using the closed itemset lattice framework, we show that this problem can be reduced to the problem of finding frequent closed itemsets. Based on this statement, we can construct efficient data mining algorithms by limiting the search space to the closed itemset lattice ...
Pasquier, Nicolas +3 more
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A framework for incremental generation of closed itemsets
Discrete Applied Mathematics, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Petko Valtchev +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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Closed Non-derivable Itemsets [PDF]
, 2006 Itemset mining typically results in large amounts of redundant itemsets. Several approaches such as closed itemsets, non-derivable itemsets and generators have been suggested for losslessly reducing the amount of itemsets. We propose a new pruning method based on combining techniques for closed and non-derivable itemsets that allows further reductions ...
Juho Muhonen, Hannu Toivonen
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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
doaj +1 more source
Generalized closed itemsets for association rule mining [PDF]
Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405), 2004 The output of Boolean association rule mining algorithms is often too large for manual examination. For dense datasets, it is often impractical to even generate all frequent itemsets. The closed itemset approach handles this information overload by pruning "uninteresting" rules following the observation that most rules can be derived from other rules ...
Pudi, Vikram, Haritsa, Jayant R
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An Efficient Method for Mining Closed Potential High-Utility Itemsets
IEEE Access, 2020 High-utility itemset mining (HUIM) has become a key phase of the pattern mining process, which has wide applications, related to both quantities and profits of items. Many algorithms have been proposed to mine high-utility itemsets (HUIs).
Bay Vo +5 more
doaj +1 more source
Mining strongly closed itemsets from data streams
, 2022 S.251-266We consider the problem of mining strongly closed itemsets from transactional data streams. Compactness and stability against changes in the input are two characteristic features of this kind of itemsets that make them appealing for different ...
Trabold, Daniel, Horvath, Tamas
core +1 more source
Mining frequent closed itemsets out of core [PDF]
Proceedings of the 2006 SIAM International Conference on Data Mining, 2006 Extracting frequent itemsets is an important task in many data mining applications. When data are very large, it becomes mandatory to perform the mining task by using an external memory algorithm, but only a few of these algorithms have been proposed so far.
LUCCHESE, Claudio +2 more
openaire +3 more sources