Results 151 to 160 of about 1,488,653 (205)
Analysis of sleep patterns among clinical nurses: a latent profile and association rule mining approach. [PDF]
BMC NursWei N, Hu L, Li J, Chu J.
europepmc +1 more source
Application of association rules to ball possessions in professional men's football. [PDF]
Front PsycholManeiro R +5 more
europepmc +1 more source
DiffNodesets: An efficient structure for fast mining frequent itemsets
Applied Soft Computing Journal, 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 ...
Zhi-Hong Deng
exaly +2 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
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
openaire +3 more sources
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 (
openaire +2 more sources
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
openaire +2 more sources
Efficient mining frequent itemsets algorithms
International Journal of Machine Learning and Cybernetics, 2013Efficient algorithms for mining frequent itemsets are crucial for mining association rules as well as for many other data mining tasks. It is well known that countTable is one of the most important facility to employ subsets property for compressing the transaction database to new lower representation of occurrences items. One of the biggest problem in
Marghny H. Mohamed +1 more
openaire +1 more source
2019
We present a survey of the most important algorithms that have been proposed in the context of the frequent itemset mining. We start with an introduction and overview of basic sequential algorithms, and then discuss and compare different parallel approaches based on shared-memory, message-passing, map-reduce, and the use of GPU accelerators.
Cafaro, Massimo, Pulimeno, Marco
openaire +2 more sources
We present a survey of the most important algorithms that have been proposed in the context of the frequent itemset mining. We start with an introduction and overview of basic sequential algorithms, and then discuss and compare different parallel approaches based on shared-memory, message-passing, map-reduce, and the use of GPU accelerators.
Cafaro, Massimo, Pulimeno, Marco
openaire +2 more sources
An Improved Algorithm for Frequent Itemsets Mining
2017 Fifth International Conference on Advanced Cloud and Big Data (CBD), 2017Based on the classical FP-growth algorithm about frequent itemsets mining, this paper proposes a more efficient non-recursive FPNR-growth algorithm and corresponding data structure. The experimental results show that the FPNR-growth algorithm is superior to the FP-growth algorithm, both in mining time and in storage space.
Hao Jiang, Xu He
openaire +2 more sources