arules - A Computational Environment for Mining Association Rules and Frequent Item Sets
Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases.
Bettina Grün +2 more
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Efficient Top-K Identical Frequent Itemsets Mining without Support Threshold Parameter from Transactional Datasets Produced by IoT-Based Smart Shopping Carts. [PDF]
Sensors (Basel), 2022 Rehman SU +4 more
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A First-Out Alarm Detection Method via Association Rule Mining and Correlation Analysis. [PDF]
Entropy (Basel), 2023 Li D, Cheng X.
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Generalized Closed Itemsets for Association Rule Mining
, 2003 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.
Pudi, Vikram, Haritsa, Jayant R
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LCTree-Based Approach for Mining Frequent Items in Real-Time. [PDF]
Comput Intell Neurosci, 2022 Chen J +4 more
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Incremental mining of closed inter-transaction itemsets over data stream sliding windows
, 2011 Mining inter-transaction association rules is one of the most interesting issues in data mining research. However, in a data stream environment the previous approaches are unable to find the result of the new-incoming data and the original database ...
Shih-Chuan Chiu +3 more
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Finding robust itemsets under subsampling
, 2013 Mining frequent patterns is plagued by the problem of pattern explosion, making pattern reduction techniques a key challenge in pattern mining. In this article we propose a novel theoretical framework for pattern reduction by measuring the robustness of ...
Calders, T.G.K. +8 more
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, 2008 Dalam dunia retail, pihak manajemen dapat memanfaatkan pengetahuan yang dapat dianalisis dari basis data retail untuk memahami pola kebutuhan pelanggan. Informasi ini dapat digunakan untuk membantu membuat keputusan bisnis.
Djunaidy, Arif, Absari, Dhiani Tresna
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TKFIM: Top-K frequent itemset mining technique based on equivalence classes. [PDF]
PeerJ Comput Sci, 2021 Iqbal S +5 more
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Research Track Poster CFI-Stream: Mining Closed Frequent Itemsets in Data Streams
, 2008 Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent closed itemsets, but they are mainly intended for traditional transaction ...
Nan Jiang
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