Cluster-Based Relationships and Metadata Registries
نویسنده
چکیده
In the course of analyzing a wide variety of knowledge-based systems, Pragati has found many types of cluster-based relationships that can enable analysts and developers to comprehend, maintain, and reuse such systems more effectively. Pragati’s cluster-based analysis of numerous knowledge-based systems through its Multi-ViewPoint Clustering Analysis (MVP-CA) Tool [Mehrotra & Bobrovnikoff 2002] has demonstrated that clustering can expose a wide variety of relationships between formally represented concepts. These include templatization and refactoring opportunities, exposition of idioms, such as inverse rules, idempotent rules, and potential inter-system mappings.
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