Graded Galois Lattices and Closed Itemsets [PDF]
Iranian Journal of Science and Technology, Transactions A: Science, 2021 15 pages, 2 figures, 1 table, derived from the Ph.D ...
Reza Sotoudeh +2 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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A global constraint for closed itemset mining
CoRR, 2016 Discovering the set of closed frequent patterns is one of the fundamental problems in Data Mining. Recent Constraint Programming (CP) approaches for declarative itemset mining have proven their usefulness and flexibility. But the wide use of reified constraints in current CP approaches raises many difficulties to cope with high dimensional datasets ...
Mehdi Maamar +3 more
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An efficient colossal closed itemset mining algorithm for a dataset with high dimensionality
Journal of King Saud University: Computer and Information Sciences, 2022 The greater interest of research in the field of bioinformatics and the ample amount of available data across the different domains paved the way for the generation of the dataset with high dimensionality.
Manjunath K. Vanahalli, Nagamma Patil
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Modified GUIDE (LM) algorithm for mining maximal high utility patterns from data streams [PDF]
International Journal of Computational Intelligence Systems, 2015 High utility pattern mining is an emerging research topic in the data mining field. Unlike frequent pattern mining, high utility pattern mining deals with non-binary databases, in which the information about purchased quantities of items is maintained ...
Chiranjeevi Manike, Hari Om
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Incremental Closed Frequent Itemsets Mining-Based Approach Using Maximal Candidates
IEEE AccessIncremental frequent itemset mining aims to efficiently update frequent itemsets without recalculating them from scratch, making it suitable for streaming data and real-time analytics.
Mohammed A. Al-Zeiadi +1 more
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New and Efficient Algorithms for Producing Frequent Itemsets with the Map-Reduce Framework
Algorithms, 2018 The Map-Reduce (MR) framework has become a popular framework for developing new parallel algorithms for Big Data. Efficient algorithms for data mining of big data and distributed databases has become an important problem.
Yaron Gonen, Ehud Gudes, Kirill Kandalov
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TT-Miner: Topology-Transaction Miner for Mining Closed Itemset
IEEE Access, 2019 Mining frequent closed itemsets (FCIs) from transaction databases is a fundamental problem in many data mining applications. All the enumeration algorithms enumerate FCIs by adding a singleton item to an itemset and then checking whether it is closure ...
Bo Li +3 more
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A novel biclustering approach to association rule mining for predicting HIV-1-human protein interactions. [PDF]
PLoS ONE, 2012 Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions.
Anirban Mukhopadhyay +2 more
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Efficient Algorithms for Mining Closed and Maximal High Utility Itemsets [PDF]
, 2022 Closed high utility itemsets (CHUIs) and maximal high utility itemsets (MaxHUIs) are two important concise representations of HUIs. Discovering these itemsets is important because they are lossless and compact, i.e., they provide a concise summary of all
Dương, Văn Hải +2 more
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