Business Intelligence

Sequential Pattern Mining Using Apriori Algorithm & Frequent Pattern Tree Algorithm

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Executive Summary

The concept of Sequential Pattern Mining was first introduced by Rakesh Agrawal and Ramakrishnan Srikant in the year 1995. Sequential Patterns are used to discover sequential sub-sequences among large amount of sequential data. In web usage mining, Sequential Patterns are exploited to find sequential navigation patterns that appear in users' sessions sequentially. The information obtained from sequential pattern mining can be used in marketing, medical records, sales analysis, and so on. In this paper, a new algorithm is proposed; it combines the Apriori algorithm and FP-tree structure which proposed in FP-growth algorithm. The advantage of proposed algorithm is that it dosen't need to generate conditional pattern bases and sub-conditional pattern tree recursively. And the results of the experiments show that it works faster than Apriori.

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