An algorithm for mining association rules based on big data

2014 ◽  
Author(s):  
Mouzhong Liu ◽  
Min Sun
Keyword(s):  
Big Data ◽  
Association Rules ◽  
Mining Association Rules

Mining association rules on Big Data through MapReduce genetic programming

2017 ◽  
Vol 25 (1) ◽  
pp. 31-48 ◽  
Author(s):  
F. Padillo ◽  
J.M. Luna ◽  
F. Herrera ◽  
S. Ventura
Keyword(s):  
Big Data ◽  
Genetic Programming ◽  
Association Rules ◽  
Mining Association Rules

Mining association rules in big data with NGEP

2015 ◽  
Vol 18 (2) ◽  
pp. 577-585 ◽  
Author(s):  
Yunliang Chen ◽  
Fangyuan Li ◽  
Junqing Fan
Keyword(s):  
Big Data ◽  
Association Rules ◽  
Mining Association Rules

scholarly journals Dynamic Horizontal Union Algorithm for Multiple Interval Concept Lattices

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 159 ◽  
Author(s):  
Yafeng Yang ◽  
Ru Zhang ◽  
Baoxiang Liu
Keyword(s):  
Big Data ◽  
Real Time ◽  
Association Rules ◽  
Lattice Structure ◽  
Concept Lattice ◽  
Concept Lattices ◽  
Generation Algorithm ◽  
Mining Association Rules ◽  
Necessary And Sufficient

In the era of big data, the data is updating in real-time. How to prepare the data accurately and efficiently is the key to mining association rules. In view of the above questions, this paper proposes a dynamic horizontal union algorithm of multiple interval concept lattices under the same background of the different attribute set and object set. First, in order to ensure the integrity of the lattice structure, the interval concept lattice incremental generation algorithm was improved, and then interval concept was divided into existing concept, redundancy concept and empty concept. Secondly, combining the characteristics of the interval concept lattice, the concept of consistency of interval concept lattice was defined and it is necessary and sufficient for the horizontal union of the lattice structure. Further, the interval concepts united were discussed, and the principle of horizontal unions was given. Finally, the sequence was scanned by the traversal method. This method increased the efficiency of horizontal union. A case study shows the feasibility and efficiency of the proposed algorithm.

scholarly journals Protecting big data mining association rules using fuzzy system

2019 ◽  
Vol 17 (6) ◽  
pp. 3057
Author(s):  
Gandikota Ramu ◽  
M Soumy ◽  
Appawala Jayanthi ◽  
J. Somasekar ◽  
K. K. Baseer
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Association Rules ◽  
Fuzzy System ◽  
Big Data Mining ◽  
Mining Association Rules
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