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Scalable Parallel Data Mining for Association Rules

Summary: Two parallel algorithms for scalable association-rule mining. Intelligent Data Distribution partitions candidates with efficient IPC; Hybrid Distribution adds dynamic load balancing, yielding linear scaling and higher rule yield per scan on Cray T3D. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3015
Venue
SIGMOD
Year
1997
Pagerank
6.5917463e-05
Overall Rank
4,640 | 68.17%
DOI
10.1145/253260.253330

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{han_sigmod97,
        title = {{Scalable Parallel Data Mining for Association Rules}},
        author = {Han, Eui-Hong (Sam) and Karypis, George and Kumar, Vipin},
        series = {{SIGMOD} '97},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/253260.253330},
        url = {https://dl.acm.org/doi/10.1145/253260.253330},
        year = {1997}
}

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