MVEMFI: Visualizing and Extracting Maximal Frequent Itemsets
نویسندگان
چکیده
Association rule is a data mining technique that has a huge number of applications. One of the crucial steps in association rule is the extraction of frequent itemsets. This research is inspired by simple appealing visualization of itemsets frequencies in the simple well known two dimension matrix representations. This paper proposes a new procedure to extract maximal frequent itemsets called Matrix Visualization and Extraction of Maximal Frequent Itemsets. The procedure consists of two steps. The first step sets the environment to mine data while the second extracts frequent itemsets. MVEMFI procedure has been tested by three synthetic datasets and processing time has been recorded. It has been found that MVEMFI performance is not affected by the number of transactions or the density of items’ occurrences in the dataset.
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