General purpose computation using Graphic Processing Units (GPUs) is a well‐established
research area focusing on high‐performance computing solutions for massively …

Pattern mining is a fundamental technique of data mining to discover interesting correlations
in the data set. There are several variations of pattern mining, such as frequent itemset …

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 …

Abstract Exact approaches to Frequent Itemsets Mining (FIM) are characterised by poor
runtime performance when dealing with large database instances. Several FIM bio-inspired …

This paper explores advances in the data mining field to solve the fundamental Document
Information Retrieval problem. In the proposed approach, useful knowledge is first …

Heuristic algorithms have been developed to find approximate solutions for high-utility
itemset mining (HUIM) problems that compensate for the performance bottlenecks of exact …

This paper considers discovering frequent itemsets in transactional databases and
addresses the time complexity problem by using high performance computing (HPC). Three …

This paper provides a short overview of space–time series clustering, which can be
generally grouped into three main categories such as: hierarchical, partitioning-based, and …

Association rule mining is a popular data mining task, which has important in many domains.
Because the task of association rule mining is very time consuming, evolutionary and swarm …

Hashtag is an iconic feature to retrieve the hot topics of discussion on Twitter or other social
networks. This paper incorporates the pattern mining approaches to improve the accuracy of …