Mining Maximal Sequential Patterns

@article{Guan2005MiningMS,
  title={Mining Maximal Sequential Patterns},
  author={En-Zheng Guan and Xiao-Yu Chang and Zhe Wang and Chun-guang Zhou},
  journal={2005 International Conference on Neural Networks and Brain},
  year={2005},
  volume={1},
  pages={525-528}
}
To solve the problem that when patterns are long, frequent sequential patterns mining may generate an exponential number of results, which often makes decision-makers perplexed for there is too much useless repeated information, a novel algorithm MFSPAN (maximal frequent sequential pattern mining algorithm) to mine the complete set of maximal frequent sequential patterns in sequence databases is proposed. MFSPAN takes full advantage of the property that two different sequences may share a… CONTINUE READING
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