The shifting algorithm technique for the partitioning of trees
Discrete Applied Mathematics - Special volume on partitioning and decomposition in combinatorial optimization
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Controlled Vocabularies in OODBs: Modeling Issues and Implementation
Distributed and Parallel Databases
Identifying a Forest Hierarchy in an OODB Specialization Hierarchy Satisfying Disciplined Modeling
COOPIS '96 Proceedings of the First IFCIS International Conference on Cooperative Information Systems
Cluster Analysis
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Controlled medical vocabularies have become increasingly important in a range of medical informatics applications. However, the extensive size of most vocabularies often makes it diffcult for users to gain an understanding of their contents. In previous work, we have investigated the partitioning of a large semantic-network based medical vocabulary into smaller units, for the purpose of easier graphical display and comprehension. The partitioning process relied heavily on a domain expert. In this paper, we propose a structural method for automating the partitioning of a vocabulary. The structural method is based on a definition of the similarity of a pair consisting of a child concept and its parent concept in the semantic network. A distribution over these similarities for all pairs in the semantic network is then computed. Based on this distribution, the semantic network can be partitioned into more manageable pieces. The approach has been applied to the InterMED and a complex portion of the MED, two large medical vocabularies.