Association rules mining has been largely studied by the data mining community. ARM aims
to extract the interesting rules from any given transactional database. This problem is well …

In stock marketing, picking the right stock depends on the true stock value and the ability to
pick the stock is crucial as it influences the profit of investors. Data mining techniques have …

Association rules mining (ARM) is an unsupervised learning task. It is used to generate
significant and relevant association rules among items in a database. APRIORI and FP …

Genetic algorithms (GA) are widely used in the literature to extract interesting association
rules. However, they are time consuming mainly due to the growing size of databases. To …

Finding frequent itemsets is a popular data mining problem, aiming to extract hidden
patterns from a transactional database. Several bio-inspired approaches to solve this …

Association rules mining has attracted a lot of attention in the data mining community. It aims
to extract the interesting rules from any given transactional database. This paper deals with …

This paper deals with association rules mining using evolutionary algorithms. All previous
bio-inspired based association rules mining approaches generate non admissible rules …

“Particle Swarm Optimization”(PSO),“Artificial Bee Colony algorithm”(ABC) are the typical
example of evolutionary algorithm. In this paper pre-processing was done initially to clean …

Association rule mining is a technique of generating frequent item sets so that the analysis
on the basis of these sets can be used for different application areas such as analysis of …

On the commercial radio station, the advertising schedule is done manually, which resulted
in ineffectiveness of ads schedule. Playback time consists of two types such as prime time …