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- W1986238488 abstract "Dependency analysis is an important but computationally demanding problem in all empirical science. It is especially problematic in bioinformatics, where data sets are often high dimensional, dense and/or strongly correlated.As a solution, we introduce a new algorithm which searches the most significant association rules expressing positive dependencies. The algorithm uses several effective pruning principles, which enable search without any minimum frequency thresholds. According to our initial experiments, the algorithm suits especially well for typical biological and medical data sets." @default.
- W1986238488 created "2016-06-24" @default.
- W1986238488 creator A5077299041 @default.
- W1986238488 date "2009-06-28" @default.
- W1986238488 modified "2023-09-26" @default.
- W1986238488 title "Lift-based search for significant dependencies in dense data sets" @default.
- W1986238488 cites W1979356656 @default.
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- W1986238488 doi "https://doi.org/10.1145/1562090.1562093" @default.
- W1986238488 hasPublicationYear "2009" @default.
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