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Dynamic Itemset Counting and Implication Rules for Market Basket Data

Summary: Dynamic itemset counting for market-basket data with fewer passes than classic algorithms and fewer candidates than sampling-based methods, aided by item reordering for efficiency. Introduces a normalized implication-rule framework that yields true implications based on both antecedent and consequent, showing real-data characteristics strongly affect performance and results. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hc47412636e931fb5
Venue
SIGMOD
Year
1997
Pagerank
0.00014470041
Overall Rank
723 | 95.16%
DOI
10.1145/253260.253325

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{brin_sigmod97,
        title = {{Dynamic Itemset Counting and Implication Rules for Market Basket Data}},
        author = {Brin, Sergey and Motwani, Rajeev and Ullman, Jeffrey D. and Tsur, Shalom},
        series = {{SIGMOD} '97},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/253260.253325},
        url = {https://dl.acm.org/doi/10.1145/253260.253325},
        year = {1997}
}

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Rank Citing Paper Year Venue Pagerank
153 New Sampling-Based Summary Statistics for Improving Approximate Query Answers 1998 SIGMOD 0.0002855087
310 Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications 1998 SIGMOD 0.00021410542
591 Computing Iceberg Queries Efficiently 1998 VLDB 0.00015853273
653 Discovering Data Quality Rules 2008 VLDB 0.00015102328
914 Efficiently Mining Long Patterns from Databases 1998 SIGMOD 0.00013081245
1,008 Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications 1998 SIGMOD 0.00012527069
1,759 Clustering Categorical Data: An Approach Based on Dynamical Systems 1998 VLDB 9.6978328e-05
1,768 Semantic Compression and Pattern Extraction with Fascicles 1999 VLDB 9.6803078e-05
4,199 Traversing Itemset Lattices with Statistical Metric Pruning 2000 PODS 6.7299701e-05
4,467 Online Association Rule Mining 1999 SIGMOD 6.5739122e-05
5,774 A New Framework For Itemset Generation 1998 PODS 5.9812275e-05
6,918 REDS: Rule Extraction for Discovering Scenarios 2021 SIGMOD 5.6316314e-05
7,376 A Framework for Measuring Changes in Data Characteristics 1999 PODS 5.5239044e-05
9,425 Feasible Itemset Distributions in Data Mining: Theory and Application 2003 PODS 5.1672232e-05
9,645 Discovering Top-k Rules using Subjective and Objective Criteria 2023 SIGMOD 5.1332977e-05
11,188 SHARQ: Explainability Framework for Association Rules on Relational Data 2025 SIGMOD 4.9605343e-05
12,796 Using Sentinel Technology in the TARGIT BI Suite 2010 VLDB 4.9605343e-05
12,886 An Audit Environment for Outsourcing of Frequent Itemset Mining 2009 VLDB 4.9605343e-05
13,219 Mining Frequent Itemsets Using Support Constraints 2000 VLDB 4.9605343e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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