Partitioning a vocabulary's IS-A hierarchy into trees.
Huanying Gu, Yehoshua Perl, James Geller, Michael Halper, James J. Cimino, Mansnimar Singh
Abstract
Huanying Gu, Yehoshua Perl, James Geller, Michael Halper, James J. Cimino, Mansnimar Singh
Abstract
Controlled medical vocabularies are useful in application areas such as medical information-systems and decision-support. However, such vocabularies are large and complex, and working with them can be daunting. It is important to provide a means for orienting users to the vocabulary's contents. This paper introduces a methodology for partitioning a vocabulary into small, meaningful pieces. The partitioning is done with respect to the vocabulary's IS-A hierarchy. The methodology, based on a set of rules for refining the IS-A hierarchy, is a process carried out by a user in conjunction with the computer. The methodology is demonstrated on a complex portion of a vocabulary.
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Controlled medical vocabularies are useful in application areas such as medical information-systems and decision-support. However, such vocabularies are large and complex, and working with them can be daunting. It is important to provide a means for orienting users to the vocabulary's contents. This paper introduces a methodology for partitioning a vocabulary into small, meaningful pieces. The partitioning is done with respect to the vocabulary's IS-A hierarchy. The methodology, based on a set of rules for refining the IS-A hierarchy, is a process carried out by a user in conjunction with the computer. The methodology is demonstrated on a complex portion of a vocabulary.
Key concepts: Vocabulary, Hierarchy, Computer science, Set (abstract data type), Controlled vocabulary, Process (computing), Conjunction (astronomy), Analytic hierarchy process