Results 91 to 100 of about 2,597 (181)
Mining Frequent Closed Itemsets with the Frequent Pattern List
, 2008 The mining of the complete set of frequent itemsets will lead to a huge number of itemsets. Fortunately, this problem can be reduced to the mining of frequent closed itemsets (FCIs), which results in a much smaller number of itemsets.
Ching-chi Hsu +2 more
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DiffNodesets: An efficient structure for fast mining frequent itemsets
, 2016 Mining frequent itemsets is an essential problem in data mining and plays an important role in many data mining applications. In recent years, some itemset representations based on node sets have been proposed, which have shown to be very efficient for ...
Deng, Zhi-Hong
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Mining frequent generalized itemsets and generalized association rules without redundancy [PDF]
, 2008 This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules).
Gene Cooperman +3 more
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Class Association Rule Pada Metode Associative Classification
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2011 Frequent patterns (itemsets) discovery is an important problem in associative classification rule mining. Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP)-growth, and Transaction Data Location (Tid)-list ...
Eka Karyawati, Edi Winarko
doaj +1 more source
Parallel algorithms for mining of frequent itemsets
CoRR, 2021 In the recent decade companies started collecting of large amount of data. Without a proper analyse, the data are usually useless. The field of analysing the data is called data mining. Unfortunately, the amount of data is quite large: the data do not fit into main memory and the processing time can become quite huge.
openaire +2 more sources
cdeNDI:a Efficient Algorithm for Mining Frequent Itemsets
, 2007 頻繁項目集的探勘，也就是從大型資料庫中找出頻繁項目集。這是許多其他問題的根本和基礎，像是關連規則、循序規則、分類和許多其他的課題。 在過去十年來，這個問題已經有了很大的進展。許多的演算法或改進現有演算法都不斷的被提出。然而，當我們降低最低支持度或是當我們遇到的資料庫是高度關連的時候，頻繁項目集的數目可能會極大。因此，如何應付密集資料庫仍然是一各具挑戰性的課題。 在這篇論文裡，我們提出cdeNDI這一種新演算法。這是以Eclat這個演算法為基礎，將closed itemsets和non ...
Huang, Chien-Ming, 黃健銘
core
Frequent Itemsets Mining with Chemical Reaction Optimization Metaheuristic
, 2018 International audienceFrequent Itemsets mining is a key concept in Association Rule Mining task, it aims to discover the frequent itemsets in a transactional dataset.Nowadays large amounts of data needs to be analysed, thus the use of traditional ...
Abdesslem Layeb +5 more
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Quick mining in dense data: applying probabilistic support prediction in depth-first order [PDF]
PeerJ Computer ScienceFrequent itemset mining (FIM) is a major component in association rule mining, significantly influencing its performance. FIM is a computationally intensive nondeterministic polynomial time (NP)-hard problem.
Muhammad Sadeequllah +3 more
doaj +2 more sources
Mining of Global Maximum Frequent Itemsets Based on FP-Tree
, 2011 As far as we know, a little research of mining global maximum frequent itemsets has been done. The paper proposed an algorithm for mining global maximum frequent itemsets based on FP-tree, namely, AMGMFI algorithm.
Bo He
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An efficient approach for interactive mining of frequent itemsets
, 2005 There have been many studies on efficient discovery of frequent itemsets in large databases. However, it is nontrivial to mine frequent itemsets under interactive circumstances where users often change minimum support threshold (minsup) because the ...
Xin Li +8 more
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