Detecting missing IS-A relations in the NCI Thesaurus using an enhanced hybrid approach.

ABSTRACT:

Background

The National Cancer Institute (NCI) Thesaurus provides reference terminology for NCI and other systems. Previously, we proposed a hybrid prototype utilizing lexical features and role definitions of concepts in non-lattice subgraphs to identify missing IS-A relations in the NCI Thesaurus. However, no domain expert evaluation was provided in our previous work. In this paper, we further enhance the hybrid approach by leveraging a novel lexical feature-roots of noun chunks within concept names. Formal evaluation of our enhanced approach is also performed.

Method

We first compute all the non-lattice subgraphs in the NCI Thesaurus. We model each concept using its role definitions, words and roots of noun chunks within its concept name and its ancestor's names. Then we p

SUBMITTER: Zheng F 

PROVIDER: S-EPMC7737275 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature