Abstract Association Rule Mining (ARM) is a significant task for discovering frequent patterns
in data mining. It has achieved great success in a plethora of applications such as market …

Nowadays, there is an increasing demand in mining interesting patterns from the big data.
The process of analyzing such a huge amount of data is really computationally complex task …

Numerical association rule mining problem attracts the attention of researchers because of
the various applications and its importance in our world with the fast growth of the stored …

Multilevel association rules mining is an important domain to discover interesting relations
between data elements with multiple levels abstractions. Most of the existing algorithms …

Multilevel association rule mining in distributed environment plays an important role in big
data analysis for making marketing strategy. Multilevel association rule provides more …

Power consumption is a major factor to be taken into consideration when using mobile
devices in the IoT field. Good Power management requires proper understanding of the way …

In this work, association rules are optimized by using improved particle swarm optimization
algorithm (PSO Algorithm). Here improved PSO algorithm means classical PSO algorithm …

Many association rule mining algorithms have been well-established, such as Apriori, Eclat,
FP-Growth, or LCM algorithms. However, the challenge is that the huge size of association …

Nowadays, detecting and interpreting random variation extracted from satellite image time
series is a far-reaching real-world issue. A more adequate approach should be designed to …

In data mining, Association rule mining is one of the popular and simple method to find the
frequent item sets from a large dataset. While generating frequent item sets from a large …