3 Proposed Techniques – An Overview 4 3.1 Matrix Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.1.1 Global Threshold Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.1.2 Local Threshold Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.1.3 Michaelis-Menten Reduction . . . . . . . . . . . . . . . . . . . . . . . ....

We introduce MiningZinc, a general framework for constraint-based pattern mining, one of the most popular tasks in data mining. MiningZinc consists of two key components: a language component and a toolchain component. The language allows for high-level and natural modeling of mining problems, such that MiningZinc models closely resemble definitions found in the data mining literature. It is in...

We present an algorithm that progressively generates canonical Sums Of Products (SOPs) for completelyand incompletely-specified Boolean functions using a satisfiability solver. The progressive generation allows for real time monitoring and early termination, as well as for generation of partial SOPs for specific incremental applications. On the other hand, canonicity brings independence of the ...