Results 91 to 100 of about 2,690 (229)
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
core
Mining Frequent Itemsets with Category-Based Constraints
, 2003 The discovery of frequent itemsets is a fundamental task of association rule mining. The challenge is the computational complexity of the itemset search space. One of the solutions for this is to use constraints to focus on some specific itemsets.
Hui, Siu Cheung +5 more
core +1 more source
FREQUENT ITEMSETS MINING FOR BIG DATA
, 2019 Frequent Itemsets Mining (FIM) is a fundamental mining model and plays an important role in Data Mining. It has a vast range of application fields and can be employed as a key calculation phase in many other mining models such as Association Rules, Correlations, Classifications, etc. Generally speaking, FIM counts the frequencies of co-occurrence items,
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
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
core +1 more source
Mining frequent itemsets from uncertain data
, 2007 We study the problem of mining frequent itemsets from uncertain data under a probabilistic framework. We consider transactions whose items are associated with existential probabilities and give a formal definition of frequent patterns under such an ...
Kao, B, Chui, CK, Hung, E
core
Frequent Itemset Mining in Big Data With Effective Single Scan Algorithms
IEEE Access, 2018 This paper considers frequent itemsets mining in transactional databases. It introduces a new accurate single scan approach for frequent itemset mining (SSFIM), a heuristic as an alternative approach (EA-SSFIM), as well as a parallel implementation on ...
Youcef Djenouri +3 more
doaj +1 more source
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
core +1 more source
Constraint Programming for Mining Borders of Frequent Itemsets
, 2019 International audienceFrequent itemset mining is one of the most studied tasks in knowledge discovery. It is often reduced to mining the positive border of frequent itemsets, i.e. maximal frequent itemsets.
Christian Bessiere +5 more
core +1 more source
A partition enhanced mining algorithm for distributed association rule mining systems
Egyptian Informatics Journal, 2015 The extraction of patterns and rules from large distributed databases through existing Distributed Association Rule Mining (DARM) systems is still faced with enormous challenges such as high response times, high communication costs and inability to adapt
A.O. Ogunde, O. Folorunso, A.S. Sodiya
doaj +1 more source