The use of association rule mining techniques has become a focal point for many researchers seeking better understanding consumer behavior. By analyzing the relationships between products and their placement in aisles, valuable insights can be gained into factors that influence product preservation large-scale distribution environments. This approach potential to inform decision-making processe...

The association rule mining technique emerged with the objective to find novel, useful, and previously unknown associations from transactional databases, and a large amount of association rule mining algorithms have been proposed in the last decade. Their main drawback, which is a well known problem, is the generation of large amounts of frequent patterns and association rules. In geographic da...

In this paper we present the various elementary traversal approaches for mining association rules. We start with a formal definition of association rule and its basic algorithm. We then discuss the association rule mining algorithms from several perspectives such as breadth first approach, depth first approach and Hybrid approach. Comparison of the various approaches is done in terms of time co...

Rule mining is very important for data mining. However, traditional association rule is relatively weak in semantic representation. To address it, the main contributions of this paper included: (1) proposing formal concepts on hDimensional Enhanced Semantic Association Rule (h-DESAR) with selfcontained logic operator; (2) proposing the h-DESAR mining method based on Immune-based Gene Expression...

Privacy is an important issue when one wants to make use of data that involves individuals’ sensitive information. Research on protecting the privacy of individuals and the confidentiality of data has received contributions from many fields, including computer science, statistics, economics, and social science. In this paper, we survey research work in privacy-preserving Data Publishing and Ass...