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FARMER: Finding Interesting Rule Groups in Microarray Datasets

Summary: FARMER handles microarray data with many columns and few rows by mining rule groups tied to common row sets rather than single rules. Exploring row enumeration and applying min support, confidence, and chi-square, FARMER prunes and beats prior rule mining on data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hf5c0dc8b99f6318a
Venue
SIGMOD
Year
2004
Pagerank
4.9793485e-05
Overall Rank
13,055 | 12.23%
DOI
10.1145/1007568.1007587

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{cong_sigmod04,
        title = {{FARMER: Finding Interesting Rule Groups in Microarray Datasets}},
        author = {Cong, Gao and Tung, Anthony K. H. and Xu, Xin and Pan, Feng and Yang, Jiong},
        series = {{SIGMOD} '04},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1007568.1007587},
        url = {https://dl.acm.org/doi/10.1145/1007568.1007587},
        year = {2004}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
3,902 CSV: Visualizing and Mining Cohesive Subgraphs 2008 SIGMOD 6.9340634e-05
13,019 Mining Top-k Covering Rule Groups for Gene Expression Data 2005 SIGMOD 4.9793485e-05
14,217 Semantic Mining and Analysis of Gene Expression Data 2004 VLDB -
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Outgoing Citations (Sorted by Pagerank)

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

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