Results 11 to 20 of about 2,974 (185)
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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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 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
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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
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High Quality, Efficient Hierarchical Document Clustering Using Closed Interesting Itemsets [PDF]
, 2006 High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to improve the efficiency of hierarchical document clustering. In this paper,
Kender, John R., Malik, Hassan H.
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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
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ETP-Mine: An Efficient Method for Mining Transitional Patterns [PDF]
, 2010 A Transaction database contains a set of transactions along with items and their associated timestamps. Transitional patterns are the patterns which specify the dynamic behavior of frequent patterns in a transaction database.
Bhaskar, A., Kumar, B. Kiran
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arules - A Computational Environment for Mining Association Rules and Frequent Item Sets
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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FCHUIM: Efficient Frequent and Closed High-Utility Itemsets Mining
IEEE Access, 2020 Mining a closed high-utility itemset is a prevalent research task in analyzing transaction databases. However, numerous target itemsets are generated in the closed high-utility itemset mining task.
Tianyou Wei +5 more
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Efficiently mining association rules based on maximum single constraints
Vietnam Journal of Computer Science, 2017 A serious problem encountered during the mining of association rules is the exponential growth of their cardinality. Unfortunately, the known algorithms for mining association rules typically generate scores of redundant and duplicate rules. Thus, we not
Anh Tran, Tin Truong, Bac Le
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