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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
3514
Venue
SIGMOD
Year
2004
Pagerank
4.1945683e-05
Overall Rank
12,572 | 12.54%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
3,480 CSV: Visualizing and Mining Cohesive Subgraphs 2008 SIGMOD 7.0538737e-05
12,536 Mining Top-k Covering Rule Groups for Gene Expression Data 2005 SIGMOD 4.1945683e-05
13,705 Semantic Mining and Analysis of Gene Expression Data 2004 VLDB -
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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.

Rank Cited Paper Year Venue Pagerank
36 Fast Algorithms for Mining Association Rules 1994 VLDB 0.00076161096
472 Bottom-Up Computation of Sparse and Iceberg CUBEs 1999 SIGMOD 0.00022346384
1,455 RainForest - A Framework for Fast Decision Tree Construction of Large Datasets 1998 VLDB 0.00011899821
1,626 Exploratory Mining and Pruning Optimizations of Constrained Association Rules 1998 SIGMOD 0.00011094469
3,454 Traversing Itemset Lattices with Statistical Metric Pruning 2000 PODS 7.0778482e-05
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