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Ratio Rules: A New Paradigm for Fast, Quantifiable Data Mining

Summary: Ratio Rules introduce a quantifiable data-mining paradigm using guessing-error (RMSE) for matrix reconstruction. A single-pass computation enables forecasting, what-if, and missing-value guessing, with up to 5× lower error than baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8467
Venue
VLDB
Year
1998
Pagerank
4.9216736e-05
Overall Rank
6,784 | 52.86%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
4,805 Optimization of Constrained Frequent Set Queries with 2-variable Constraints 1999 SIGMOD 5.9050441e-05
8,786 Adding Counting Quantifiers to Graph Patterns 2016 SIGMOD 4.4467423e-05
9,292 Analyzing Quantitative Databases: Image is Everything 2001 VLDB 4.3581013e-05
12,696 Data Mining on an OLTP System (Nearly) for Free 2000 SIGMOD 4.1905499e-05
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Showing 8 of 8 cited papers.

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

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