Over the past few decades, business analytics has been widely used in various business
sectors and has been effective in increasing enterprise value. With the advancement of …

The frequent itemset mining (FIM) is one of the most important techniques to extract
knowledge from data in many real-world applications. The Apriori algorithm is the widely …

Frequent Itemsets and Association Rules Mining (FIM) is a key task in knowledge discovery
from data. As the dataset grows, the cost of solving this task is dominated by the component …

Nowadays, there is an increasing demand to monitor, analyze, and control large scale
distributed systems. Events detected during monitoring are temporally correlated, which is …

Today, the customer's requirements are entirely transformed. Many big retail organizations
are facing sudden decline in the sales and revenues caused due to indecisive and erratic …

Presently, retailing has changed its face from unordered stacked traditional stores to
beautifully decorated and appropriately managed merchandise stores or shopping malls …

Association rule mining remains a very popular and effective method to extract meaningful
information from large datasets. It tries to find possible associations between items in large …

Extraction of valuable data from extensive datasets is a standout amongst the most vital
exploration issues. Association rule mining is one of the highly used methods for this …

Mining frequent itemset is considered as a core activity to find association rules from
transactional datasets. Among the different well-known approaches to find frequent itemsets …

Many algorithms have proposed to solve the association rule learning problem. However,
most of these algorithms suffer from the problem of scalability either because of tremendous …