An Efficient Algorithm for Extracting Frequent Item Sets from a Data Set

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Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
Frequent item set mining is a heart favorite topic of research for many researchers over the years. It is the basis for association rule mining. Association rule mining is used in many applications like: market basket analysis, intrusion detection, privacy preserving, etc. In this paper, the authors have developed a method to discover large item sets from the transaction database. The proposed method is fast in comparison to older algorithms. Also it takes les main memory space for computation purpose.
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