Exploratory Mining and Pruning Optimizations of Constrained Association Rules
Summary: Constraint-based, human-centered exploratory mining replaces black-box association-rule mining with constrained association queries (domain, class, and SQL-style aggregates) to guide discovery. CAP uses anti-monotonicity and succinctness to classify constraints into four categories and prune aggressively, delivering up to 80× speedups. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Raymond T. Ng (University of British Columbia)
- 2. Laks V. S. Lakshmanan (Concordia University)
- 3. Jiawei Han (Simon Fraser University)
- 4. Alex Pang (University of British Columbia)
BibTeX Citation
@inproceedings{ng_sigmod98,
title = {{Exploratory Mining and Pruning Optimizations of Constrained Association Rules}},
author = {Ng, Raymond T. and Lakshmanan, Laks V. S. and Han, Jiawei and Pang, Alex},
series = {{SIGMOD} '98},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/276304.276307},
url = {https://dl.acm.org/doi/10.1145/276304.276307},
year = {1998}
}
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