The process of data mining produces various patterns from a given data source. The most
recognized data mining tasks are the process of discovering frequent itemsets, frequent …

The document data is growing at an exponential rate. It is heterogeneous, dynamic and
highly unstructured in nature. These characteristics of document data pose new challenges …

This paper provides a brief overview of the techniques used in frequent itemset mining. It
discusses the search strategies used; ie depth first vs. breadth-first, and dataset …

The knowledge discovery algorithms have become ineffective at the abundance of data and
the need for fast algorithms or optimizing methods is required. To address this limitation, the …

Mining frequent patterns is one of the most important concepts of data mining. Frequent
pattern mining has been a highly concerned field of data mining for researcher for over two …

Frequent Itemsets (FIs) mining has gained prolific research interest of the data mining
community know a days. It is considered a pivotal step for association rule mining. The …

Mining association rules between data items is essential in the discovery of knowledge
hidden in datasets. There are many efficient association rules mining algorithms. The …

This paper provides a brief overview of the techniques used in frequent itemset mining. It
discusses the search strategies used; ie depth first vs. breadth-first, and dataset …

Frequent Itemsets (FIs) mining has gained prolific research interest of the data mining
community know a days. It is considered a pivotal step for association rule mining. The …

A new algorithm, named SCan-MAX for mining distributed maximal frequent itemsets from
databases was proposed, the SCan-MAX used Sorted SCan-tree to store all the information …