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https://www.sciencedirect.com/science/article/pii/S0169023X07001875
Discovering frequent itemsets by support approximation and itemset clustering. Author links open overlay panel Kuen-Fang ... to reduce the time complexity of searching whole subsets of an itemset in support approximation. Experimental results and analyses show that the clustering technique can effectively improve mining accuracy and that CAC ...Cited by: 13
https://www.sciencedirect.com/science/article/abs/pii/S0169023X07001875
Discovering frequent itemsets by support approximation and itemset clustering. ... To overcome this drawback, in this paper we combine a new clustering method with support approximation, and propose a mining method, namely CAC, to discover frequent itemsets based on the Principle of Inclusion and Exclusion. ... Frequent itemset.Cited by: 13
https://www.researchgate.net/publication/222424242_Discovering_frequent_itemsets_by_support_approximation_and_itemset_clustering
Download Citation Discovering frequent itemsets by support approximation and itemset clustering To speed up the task of association rule mining, a novel concept based on support approximation ...
https://core.ac.uk/display/41660320
To overcome this drawback, in this paper we combine a new clustering method with support approximation, and propose a mining method, namely CAC, to discover frequent itemsets based on the Principle of Inclusion and Exclusion. The clustering technique groups highly similar members to improve the accuracy of support approximation.
https://ieeexplore.ieee.org/document/1565744/
Each cluster has only one closed itemset and is the superset of all itemsets with the same support. Number of closed itemsets is identical to the number of clusters. Therefore, the problem of discovering closed itemsets can be considered as the problem of clustering the complete set of itemsets …
https://dl.acm.org/citation.cfm?id=502539
Kuen-Fang Jea , Ming-Yuan Chang, Discovering frequent itemsets by support approximation and itemset clustering, Data & Knowledge Engineering, v.65 n.1, p.90-107, April, 2008 Shengxin Liu , Chung Keung Poon, On mining approximate and exact fault-tolerant frequent itemsets, Knowledge and Information Systems, v.55 n.2, p.361-391, May 2018Cited by: 182
https://www.researchgate.net/publication/221532273_The_identification_and_extraction_of_itemset_support_defined_by_the_weight_matrix_of_a_Self-Organising_Map
The concept of support approximation [3, 67812,20,21,32,33] is used to improve performance when discovering frequent itemsets. The method in [33] reduces the number of frequent itemsets by ...
https://t4tutorials.com/support-confidence-minimum-support-frequent-itemset-in-data-mining/
and similarly, we can calculate confidence for all itemsets. Next Similar Tutorials. Frequent pattern Mining, Closed frequent itemset, max frequent itemset in data mining – Click Here; Support, Confidence, Minimum support, Frequent itemset, K-itemset, absolute support in …
http://meta-synthesis.amss.cas.cn/Publication/MSKS_Publications/Journal_papers/PaperlistsJ/201410/P020141013624273944824.pdf
Document clustering Frequent itemsets Maximum capturing Similarity measure Competitive learning abstract Frequent itemset originates from association rule mining. Recently, it has been applied in text mining such as document categorization, clustering, etc. In this paper, we conduct a study on text clustering using frequent itemsets.
http://www.enggjournals.com/ijcse/doc/IJCSE11-03-03-149.pdf
FREQUENT ITEMSETS USING CLUSTERING TECHNIQUES ... Keywords:Association rule,Apriori al gorithm,frequent Itemset ,clustering 1.INTRODUCTION Mining association rule is one of the recent data mining research. Association rules are used to show ... support will be deleted..The above process is repeated for C 3.Cited by: 3
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