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Cache-conscious Frequent Pattern Mining on a Modern Processor

Summary: Identifies poor locality and low ILP as key bottlenecks in frequent-pattern mining on modern CPUs. A cache-conscious prefix tree, tiling, and cache-reusing fine-grained threading deliver up to 4.8× speedup over state of the art. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
9528
Venue
VLDB
Year
2005
Pagerank
6.9837297e-05
Overall Rank
3,969 | 72.78%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{ghoting_vldb05,
        title = {{Cache-conscious Frequent Pattern Mining on a Modern Processor}},
        author = {Ghoting, Amol and Buehrer, Gregory and Parthasarathy, Srinivasan and Kim, Daehyun and Nguyen, Anthony and Chen, Yen-Kuang and Dubey, Pradeep},
        journal = {PVLDB},
        series = {{VLDB} '05},
        year = {2005}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
1,150 DimmWitted: A Study of Main-Memory Statistical Analytics 2014 VLDB 0.00011943462
1,511 Speedup Graph Processing by Graph Ordering 2016 SIGMOD 0.00010538011
8,315 ADDICT: Advanced Instruction Chasing for Transactions 2014 VLDB 5.4553606e-05
12,656 Optimization of Frequent Itemset Mining on Multiple-Core Processor 2007 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

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