Authors V. M. Kureichik, I. B. Safronenkova
Month, Year 04, 2018 @en
Index UDC 004.896
Abstract The development of new intelligent information processing methods is caused by the onrush of computer equipment. The present article shows that an automated domain ontology development is important today. Domain ontology is often used as a knowledge base “frame” in Intelligent Decision Support Systems (IDSS). The problem of engineering software benchmarking study for the purpose of fitting for task type and computational resources is important today. This problem is often solved by IDSS. It"s worth to remark that a manual ontology development is a time consuming and expensive process. Because of a great variety of circuit partitioning problem formulization, clustering is a necessary step of automated circuit partitioning problem ontology development. The automated clustering partitioning problem is caused by the problem of complex data comparison. This data is usually presented by different dimension structure. The goal of this work is the development of circuit partitioning problem clustering method based on adjacency matrix unification. The hypergraph model of circuit representation has been chosen, the circuit partitioning problem formalized. The novelty of proposed method is a different dimension matrix unification procedure inclusion into the typical clustering algorithm. The partitioning problem clustering experiments have been held. At the present stage of investigation we can conclude that the proposed method has a low computational complexity. The fundamental difference of developed method is the clustering of circuit partitioning problems that include different dimension matrix in their formalization. This permits to lead clustering automatically. The proposed method is focused on efficiency improvement of automated domain ontology development.

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Keywords Clustering, ontology; circuit partitioning; matrix; attribute vector; hypergraph circuit model; matrix similarity
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