In this paper, we explored a learning approach which combines different learning methods in inductive logic programming (ILP) to allow a learner to produce more expressive hypothese than that of each individual learner. Such a learning approach may be useful when the performance of the task depends on solving a large amount of classification problems and each has its own characteristics which may or may not fit a particular learning method. The task of sematnic parser acquisition in two different domains was attempted and preliminary results demonstrated that such an approach is promising.

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In Proceedings of the 12th European Conference on Machine Learning, pp. 466-477, Freiburg, Germany 2001.

@InProceedings{tang:ecml01, title={Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing}, author={Lappoon R. Tang and Raymond J. Mooney}, booktitle={Proceedings of the 12th European Conference on Machine Learning}, address={Freiburg, Germany}, key={CHILL ILP}, pages={466-477}, url="http://www.cs.utexas.edu/users/ai-lab?tang:ecml01", year={2001} }