Optimizing Frequency Queries for Data Mining Applications

@article{Malik2007OptimizingFQ,
  title={Optimizing Frequency Queries for Data Mining Applications},
  author={Hassan H. Malik and John R. Kender},
  journal={Seventh IEEE International Conference on Data Mining (ICDM 2007)},
  year={2007},
  pages={595-600}
}
Data mining algorithms use various Trie and bitmap-based representations to optimize the support (i.e., frequency) counting performance. In this paper, we compare the memory requirements and support counting performance of FP Tree, and Compressed Patricia Trie against several novel variants of vertical bit vectors. First, borrowing ideas from the VLDB domain, we compress vertical bit vectors using WAH encoding. Second, we evaluate the Gray code rank- based transaction reordering scheme, and… CONTINUE READING
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Optimizing Frequency Queries for Data Mining Applications

  • H. H. Malik, J. R. Kender
  • Columbia University Technical Report, CUCS-026-07
  • 2007
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  • C. Lucchese
  • al., "Fast and Memory Efficient Mining of…
  • 2006
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