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Automatic discovery of locally frequent itemsets in the presence of highly frequent itemsets
Intelligent Data Analysis, 2005Many alternatives have been proposed for the mining of association rules involving rare but 'interesting' itemsets in a dataset where there also exist highly frequent itemsets. Nevertheless, all the approaches thus far suggested that we knew which those interesting itemsets are, as well as which is the right support value for them.
Ferenc Bodon +3 more
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Reference itemsets: useful itemsets to approximate the representation of frequent itemsets
Soft Computing, 2016Deriving frequent itemsets from databases is an important research issue in data mining. The number of frequent itemsets may be unusually large when a low minimum support threshold is given. As such, the design of a compact representation to compress and describe them is an interesting topic. In the past, most related research on compact representation
Jheng-Nan Huang +2 more
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The maintenance of representative frequent itemsets
2010 International Conference on Machine Learning and Cybernetics, 2010Mining frequent itemsets is to discover the groups of items appearing always together excess of a user specified threshold from a transaction database. However, there may be many frequent itemsets existing in a transaction database, such that it is difficult to make a decision for a decision maker.
Show-Jane Yen +2 more
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Meta itemset: a new concise representation of frequent itemset
Journal of Experimental & Theoretical Artificial Intelligence, 2009The sheer size of all frequent itemsets is one challenging problem in data mining research. Based on both closed itemset and maximal itemset, meta itemset which is a new concise representation of frequent itemset is proposed. It is proved that both closed itemset and maximal itemset are special cases of meta itemset.
Wei Song 0004, Jinhong Li, Zhangyan Xu
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Discovering frequent itemsets by support approximation and itemset clustering
Data & Knowledge Engineering, 2008To speed up the task of association rule mining, a novel concept based on support approximation has been previously proposed for generating frequent itemsets. However, the mining technique utilized by this concept may incur unstable accuracy due to approximation error.
Kuen-Fang Jea, Ming-Yuan Chang
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A Maximal Frequent Itemset Algorithm
2007We present MinMax, a new algorithm for mining maximal frequent itemsets(MFI) from a transaction database. It is based on depth-first traversal and iterative. It combines a vertical tidset representation of the database with effective pruning mechanisms.
Hui Wang +3 more
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Frequent Itemset Mining for Big Data
2013 IEEE International Conference on Big Data, 2013Frequent Itemset Mining (FIM) is one of the most well known techniques to extract knowledge from data. The combinatorial explosion of FIM methods become even more problematic when they are applied to Big Data. Fortunately, recent improvements in the field of parallel programming already provide good tools to tackle this problem.
Sandy Moens +2 more
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On Maximal Frequent Itemsets Enumeration
2018Enumerating interesting patterns from data is an important data mining task. Among the set of possible relevant patterns, maximal frequent patterns is a well known condensed representation that limits at least to some extent the size of the output. Recently, a new declarative mining framework based on constraint programming (CP and satisfiability (SAT)
Saïd Jabbour +2 more
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On a visual frequent itemset mining
2009 Fourth International Conference on Digital Information Management, 2009Given a large, dense transaction database, generating interesting frequent patterns in a user friendly manner remains as an important issue in data mining. It is because the minimum support, the most popular statistical significance measurement, is not capable of reflecting the domain user's interest. This paper presents visual frequent itemset mining (
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Mining Frequent and Homogeneous Closed Itemsets
2016It is well known that when mining frequent itemsets from a transaction database, the output is usually too large to be effectively exploited by users. To cope with this difficulty, several forms of condensed representations of the set of frequent itemsets have been proposed, among which the notion of closure is one of the most popular.
Inès Hilali +4 more
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