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Mining Top-k Covering Rule Groups for Gene Expression Data

Summary: Proposes Top-k Covering Rule Groups to mine gene-expression data per row, skipping column enumeration and yielding speedups. Presents RCBT, a classifier from top-k rule groups with a bounded set, achieving competitive accuracy and disease insights. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3675
Venue
SIGMOD
Year
2005
Pagerank
4.1945683e-05
Overall Rank
12,536 | 12.79%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
3,480 CSV: Visualizing and Mining Cohesive Subgraphs 2008 SIGMOD 7.0538737e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 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
181 Mining Frequent Patterns without Candidate Generation 2000 SIGMOD 0.00036992674
1,626 Exploratory Mining and Pruning Optimizations of Constrained Association Rules 1998 SIGMOD 0.00011094469
12,572 FARMER: Finding Interesting Rule Groups in Microarray Datasets 2004 SIGMOD 4.1945683e-05
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