A Survey on Approaches for Mining Frequent Itemsets

  • Neelima S
  • Satyanarayana N
  • et al.
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Abstract

Data mining is gaining importance due to huge amount of data available. Retrieving information from the warehouse is not only tedious but also difficult in some cases. The most important usage of data mining is customer segmentation in marketing, shopping cart analyzes, management of customer relationship, campaign management, Web usage mining, text mining, player tracking and so on. In data mining, association rule mining is one of the important techniques for discovering meaningful patterns from large collection of data. Discovering frequent itemsets play an important role in mining association rules, sequence rules, web log mining and many other interesting patterns among complex data. This paper presents a literature review on different techniques for mining frequent itemsets.

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Neelima, S., Satyanarayana, N., & Murthy, P. K. (2014). A Survey on Approaches for Mining Frequent Itemsets. IOSR Journal of Computer Engineering, 16(4), 31–34. https://doi.org/10.9790/0661-16473134

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