Mining Botnet Coordinated Attacks using Apriori-PrefixSpan Hybrid Algorithm

Educational Data Mining using Improved Apriori Algorithm

Educational Data Mining (EDM) is an emerging interdisciplinary research area that deals with the development of methods to explore data originating in an educational context. EDM uses different computational approaches to analyze educational data in order to study educational questions. Different data mining techniques has been applied in this area. One of the most widely used techniques in EDM...

Mining Sequential Patterns Using I-PrefixSpan

In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use sufficient data structure for Seq-Tree framework and separator database to reduce the execution time and memory usage. Thus, with I-PrefixSpan there is no in-memory database stored after index set is constructed. The experimental result shows tha...

Web Log Mining using Improved Version of Apriori Algorithm

Efficient Association Rule Mining Using Improved Apriori Algorithm

Association rule mining is a data mining technique to extract interesting relationships from large datasets [1, 2]. The efficiency of association rule mining algorithms has been a challenging research area in the domain of data mining [3]. Frequent pattern discovery, the task of finding sets of items that frequently occur together in a dataset is the most resource consuming phase of the rule mi...

Apriori Algorithm for Mining Frequent Patterns using Parallel Computing: Survey

: Apriori algorithm is useful for mining frequent pattern from large databases. Number of the techniques is used for the frequent pattern mining which associates the dataset with each other and most useful algorithms are Apriori & FP-growth algorithms. This paper presents the survey of Apriori algorithm for frequent pattern mining used to calculate the association in different data sets and app...