Machine learningMachine learning

Online FP-growth

Online FP-growth is an incremental extension of the FP-growth algorithm that mines frequent itemsets from continuously arriving transaction streams without rebuilding the full FP-tree from scratch. It updates an existing compact tree structure as new transactions arrive, making it suitable for real-time and high-velocity data environments where a full database scan is impractical.

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Sources

  1. Cheung, W. & Zaiane, O. R. (2004). Incremental Mining of Frequent Patterns Without Candidate Generation or Support Thr esholding. In Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), pp. 111–118. IEEE. link
  2. Lee, G., Yun, U. & Ryu, K. H. (2014). Sliding window based weighted maximal frequent pattern mining over data streams. Expert Systems with Applications, 41(2), 694–708. DOI: 10.1016/j.eswa.2013.07.094

Related methods

ScholarGateOnline FP-growth (Online Frequent Pattern Growth (Incremental FP-tree Mining)). Retrieved 2026-06-04 from https://scholargate.app/tr/machine-learning/online-fp-growth