Research on an Improved Association Rules Data Mining Algorithm and Its Application

2009 ◽  
pp. 1211-1219 ◽  
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Data Mining Algorithm ◽  
Mining Algorithm

scholarly journals Hierarchical mining algorithm for high dimensional spatiotemporal big data based on association rules

2021 ◽  
Vol 256 ◽  
pp. 02040
Author(s):  
Chunlei Zhou ◽  
Xinwei Dong ◽  
Liang Ji ◽  
Bijun Zhang ◽  
Zhongping Xu ◽  
...  
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Association Rules ◽  
High Dimensional ◽  
Data Mining Algorithm ◽  
Temporal Data ◽  
Processing Efficiency ◽  
Local Linear Embedding ◽  
Mining Algorithm ◽  
Spatio Temporal

The traditional data mining algorithm focuses too much on a single dimension of data time or space, ignoring the association between time and space, which leads to a large amount of computation and low processing efficiency of the mining algorithm and makes it difficult to guarantee the final data mining effect. In response to the above problems, a hierarchical mining algorithm based on association rules for high-dimensional spatio-temporal big data is proposed. Based on the traditional association rules, after establishing the association rules of spatio-temporal data, the data to be mined are cleaned for redundancy. After selecting the local linear embedding algorithm to reduce the dimensionality of the data, a hierarchical mining strategy is developed to realize high-dimensional spatio-temporal big data mining by searching frequent predicates to form a spatio-temporal transaction database. The simulation experiment results verify that the algorithm has high complexity and can effectively reduce the processing volume, which can improve the processing efficiency by at least 56.26% compared with other algorithms.

Implementation of Hierarchical Database Attributes Covering in Multidetector A-R Mining Algorithm

2012 ◽  
Vol 151 ◽  
pp. 560-564
Author(s):  
Shu Feng Jiang
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Data Mining Algorithm ◽  
Application Development ◽  
Association Rules Mining ◽  
Algorithm Efficiency ◽  
Attribute Weights ◽  
Mining Algorithm ◽  
Depth Analysis ◽  
Classical Association

With the development of artificial intelligence and data warehouse application development,Intelligent and efficient data mining technology has become the huge data bottleneck, This paper studies stratification theory improved technology to realize the property overrides hierarchical database, Data pretreatment based on the mining algorithm, Through in-depth analysis and research, Improved the A-R algorithm, Realize the problem scope expanded and improved the classical association rules mining algorithm efficiency, Based on the realization of the multilevel association rules mining based on the attribute weights of attributes covering hierarchical database mining methods,To improve the mining knowledge representation systems automation capabilities and data mining algorithm and its application to extended practical problems

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