This paper describes RAPTURE - tic knowledge bases that combines neural and symbolic learning methods. RAPTURE uses a modified version of backpropagation to refine the certainty factors of a MYCIN-style rule base and uses ID3's information gain heuristic to add new rules. Results on re-fining two actual expert knowledge bases demonstrate that this combined approach performs better than previous methods.

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Advances in Neural Information Processing Systems (NIPS) (1992).

@article{mahoney:nips92, title={Combining Neural and Symbolic Learning to Revise Probabilistic Rule Bases}, author={J. Jeffrey Mahoney and Raymond J. Mooney}, booktitle={Advances in Neural Information Processing Systems (NIPS) }, month={January}, url="http://www.cs.utexas.edu/users/ai-labpub-view.php?PubID=128121", year={1992} }