Knowledge Extraction from Trained Neural Networks

The artificial neural networks (ANNs) are well suitable to solve a variety class of problems in a knowledge discovery field (e.g., in natural language processing) because the trained networks are more accurate at classifying the examples that represent a problem domain. However, the neural networks that consist of large number of weighted connections (called also links) and activation units often generate the incomprehensible and hard-to-understand models. This problem may be also addressed to most powerful recurrent neural networks that employ the embedded links from a set of hidden or output units to a set of its input units.