The θ-subsumption problem is crucial to the efficiency of ILP learning systems. We discuss two θ-subsumption algorithms based on strategies for preselecting suitable matching literals. The class of clauses, for which subsumption becomes polynomial, is a superset of the deterministic clauses. We further map the general problem of θ-subsumption to a certain problem of finding a clique of fixed size in a graph, and in return show that a specialization of the pruning strategy of the Carraghan and Pardalos clique algorithm provides a dramatic reduction of the subsumption search space. We also present empirical results for the mesh design data set.
CITATION STYLE
Scheffer, T., Herbrich, R., & Wysotzki, F. (1997). Efficient θ-subsumption based on graph algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1314, pp. 212–228). Springer Verlag. https://doi.org/10.1007/3-540-63494-0_57
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