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Cited by 1,064

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Parallel mining of association rules

Agrawal, R., Shafer, J.C.·1996·IEEE Transactions on Knowledge and Data Engineering
DOI 10.1109/69.553164
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Abstract

We consider the problem of mining association rules on a shared nothing multiprocessor. We present three algorithms that explore a spectrum of trade-offs between computation, communication, memory usage, synchronization, and the use of problem specific information. The best algorithm exhibits near perfect scaleup behavior, yet requires only minimal overhead compared to the current best serial algorithm.

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Metadata

Authors
Agrawal, R., & Shafer, J. C.
Venue
IEEE Transactions on Knowledge and Data Engineering
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
1996
Volume
8
Issue
6
Pages
962-969
ISSN
1041-4347 (ISSN-L)
DOI
10.1109/69.553164
OpenAlex
W2093456341
Cited by
1,064
References
2
FWCI
53.60
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Parallel mining of association rules. https://app.cochat.ai/papers/10.1109/69.553164
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Agrawal, R., & Shafer, J. C. (1996). Parallel mining of association rules. IEEE Transactions on Knowledge and Data Engineering. https://doi.org/10.1109/69.553164

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.