Effective generalization of relational descriptions

Authors:
Larry Watanabe;Larry Rendell
Affiliations:
Beckman Institute and Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois;Beckman Institute and Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois
Venue:
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Year:
1990

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Abstract

The problem of computing maximally-specific generalizations (MSCG's) of relational descriptions can be modelled as tree search. We describe several transformations and pruning methods for reducing the complexity of the problem. Based on this analysis, we have implemented a search program (X-search) for finding the MSCG's. Experiments compare the separate and combined effects of pruning methods on search efficiency. With effective pruning methods, full-width search appears feasible for moderately sized relational descriptions.