A trie-based APRIORI implementation for mining frequent item sequences

  • Authors:
  • Ferenc Bodon

  • Affiliations:
  • Budapest University of Technology and Economics

  • Venue:
  • Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations
  • Year:
  • 2005

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Abstract

In this paper we investigate a trie-based APRIORI algorithm for mining frequent item sequences in a transactional database. We examine the data structure, implementation and algorithmic features mainly focusing on those that also arise in frequent itemset mining. In our analysis we take into consideration modern processors' properties (memory hierarchies, prefetching, branch prediction, cache line size, etc.), in order to better understand the results of the experiments.