STRUCTURE MATCHING AND TRANSFORMATION WITH DISTRIBUTED REPRESENTATIONS Tony
نویسنده
چکیده
منابع مشابه
Mining Transformation Rules for Semantic Matching
Semantic matching is finding a mapping between two knowledge representations encoded using the same ontology. Solving this matching problem is hard because the syntactic form of two knowledge representations rarely matches exactly. Previous research has shown transformation rules can be used to improve matching, but acquiring transformations is difficult. In this paper, we present an algorithm ...
متن کاملTransformation Rules for Knowledge-Based Pattern Matching
Many AI tasks require determining whether two knowledge representations encode the same knowledge. For example, rule-based classification requires matching rule antecedents with working memory; information retrieval requires matching queries with documents; and some knowledge-acquisition tasks require matching new information with already encoded knowledge to expand upon and debug both of them....
متن کاملOptimising Parallel Pattern-matching by Source-level Program Transformation
Parallel pattern-matching (PPM) provides true commutative implementation of functions defined by cases in functional languages, because no argument is given precedence over any other. However, the requirement for concurrency (in general) to support these semantics means that current implementations incur a significant performance penalty over simple, traditional left-to-right semantics. We desc...
متن کاملModel transformations in Converge
Model transformations are currently the focus of much interest and research due to the OMG’s QVT initiative. Current proposals for model transformation languages can be divided into two main camps: those taking a ‘declarative’ approach, and those opting for an ‘imperative’ approach. In this paper we detail an imperative, meta-circular, object orientated, pattern matching programming language Co...
متن کاملParallelization of Graph Transformation Based on Incremental Pattern Matching
Graph transformation based on incremental pattern matching explicitly stores all occurrences of patterns (left-hand side of rules) and updates this result cache upon model changes. This allows instantaneous pattern queries at the expense of costlier model manipulation and higher memory consumption. Up to now, this incremental approach has considered only sequential execution despite the inheren...
متن کامل