Fast and memory efficient mining of frequent closed itemsets

  title={Fast and memory efficient mining of frequent closed itemsets},
  author={Claudio Lucchese and Salvatore Orlando and Raffaele Perego},
  journal={IEEE Transactions on Knowledge and Data Engineering},
This paper presents a new scalable algorithm for discovering closed frequent itemsets, a lossless and condensed representation of all the frequent itemsets that can be mined from a transactional database. Our algorithm exploits a divide-and-conquer approach and a bitwise vertical representation of the database and adopts a particular visit and partitioning strategy of the search space based on an original theoretical framework, which formalizes the problem of closed itemsets mining in detail… CONTINUE READING
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Publications referenced by this paper.
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Zaki . Advances in Frequent Itemset Mining Implementations : Report on FIMI ’ 03

  • Bart Goethals, J. Mohammed
  • SIGKDD Explor . Newsl .
  • 2004

Efficiently using prefix-trees in mining frequent itemsets

  • Gosta Grahne, Jianfei Zhu
  • In Proceedings of the IEEE ICDM Workshop on…
  • 2003
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