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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TKFIM: Top-K frequent itemset mining technique based on equivalence classes. [PDF]
PeerJ Comput Sci, 2021 Iqbal S +5 more
europepmc +1 more source
Pruning closed itemset lattices for association rules
, 1998 Discovering association rules is one of the most important task in data mining and many efficient algorithms have been proposed in the literature. The most noticeable are Apriori, Mannila's algorithm, Partition, Sampling and DIC, that are all based on the Apriori mining method: pruning of the subset lattice (itemset lattice).
Pasquier, Nicolas +3 more
openaire +2 more sources
Status Set Sequential Pattern Mining Considering Time Windows and Periodic Analysis of Patterns. [PDF]
Entropy (Basel), 2021 Zhou S +7 more
europepmc +1 more source
Design and Implementation of a New Local Alignment Algorithm for Multilayer Networks. [PDF]
Entropy (Basel), 2022 Milano M, Guzzi PH, Cannataro M.
europepmc +1 more source
Mining actionable combined high utility incremental and associated sequential patterns. [PDF]
PLoS One, 2023 Shi M, Gong Y, Xu T, Zhao L.
europepmc +1 more source
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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Innovative Mode of Human Resource Management of University Teachers Based on Intelligent Big Data Analysis. [PDF]
Comput Intell Neurosci, 2022 Bai Y.
europepmc +1 more source
An Efficient Subset-Lattice Algorithm for Mining Closed Frequent Itemsets in Data Streams
, 2009 Online mining association rules over data streams is an important issue in the area of data mining, where an association rule means that the presence of some items in a transaction will imply the presence of other items in the same transaction. There are
Peng, Wei-hau
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DARCI: Distributed Association Rule Mining Utilizing Closed Itemsets
, 2014 A distributed rule mining algorithm must minimize the communication cost to reduce the communication bandwidth use and to improve the scalability. There are a few distributed rule mining algorithms reported in the literature.
Suad Alramouni, Jae Young Lee
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