G. Sivakumar

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We provide a simple system, based on transformation rules, which is complete for certain classes of semantic matching problems, where the equational theory with respect to which the semantic matching is performed has a convergent rewrite system. We also use this transformation system to describe decision procedures for semantic matching problems. We give(More)
A new path ordering for showing termination of associative-commutative (AC) rewrite systems is deened. If the precedence relation on function symbols is total, the ordering is total on ground terms, but unlike the ordering proposed by Rubio and Nieuwenhuis, this ordering can orient the distributivity property in the proper direction. The ordering is deened(More)
Neural Networks are successful in acquiring hidden knowledge in datasets. Their biggest weakness is that the knowledge they acquire is represented in a form not understandable to humans. Researchers tried to address this problem by extracting rules from trained Neural Networks. Most of the proposed rule extraction methods required specialized type of Neural(More)