Results 241 to 250 of about 6,573,619 (301)
Some of the next articles are maybe not open access.
2009
Data mining is a field encompassing study of the tools and techniques to assist humans in intelligently analyzing (mining) mountains of data. Data mining has found successful applications in many fields including sales and marketing, financial crime identification, portfolio management, medical diagnosis, manufacturing process management and health ...
Vasudha Bhatnagar, Sarabjeet Kochhar
openaire +1 more source
Data mining is a field encompassing study of the tools and techniques to assist humans in intelligently analyzing (mining) mountains of data. Data mining has found successful applications in many fields including sales and marketing, financial crime identification, portfolio management, medical diagnosis, manufacturing process management and health ...
Vasudha Bhatnagar, Sarabjeet Kochhar
openaire +1 more source
2005
Association Rule Mining (ARM) is concerned with how items in a transactional database are grouped together. It is commonly known as market basket analysis, because it can be likened to the analysis of items that are frequently put together in a basket by shoppers in a market. From a statistical point of view, it is a semiautomatic technique to discover
WOON, Yew-Kwong +2 more
openaire +1 more source
Association Rule Mining (ARM) is concerned with how items in a transactional database are grouped together. It is commonly known as market basket analysis, because it can be likened to the analysis of items that are frequently put together in a basket by shoppers in a market. From a statistical point of view, it is a semiautomatic technique to discover
WOON, Yew-Kwong +2 more
openaire +1 more source
2013
This chapter looks at the problem of finding any rules of interest that can be derived from a given dataset, not just classification rules as before. This is known as Association Rule Mining or Generalised Rule Induction. A number of measures of rule interestingness are defined and criteria for choosing between measures are discussed.
openaire +1 more source
This chapter looks at the problem of finding any rules of interest that can be derived from a given dataset, not just classification rules as before. This is known as Association Rule Mining or Generalised Rule Induction. A number of measures of rule interestingness are defined and criteria for choosing between measures are discussed.
openaire +1 more source
A novel hybrid GA–PSO framework for mining quantitative association rules
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2019F. Moslehi +2 more
semanticscholar +1 more source
Revisiting the rules of life for viruses of microorganisms
Nature Reviews Microbiology, 2021Adrienne M S Correa +2 more
exaly
Exploring shipping accident contributory factors using association rules
, 2019Jinxian Weng, Guorong Li
semanticscholar +1 more source