Mining non-lattice subgraphs for detecting missing hierarchical relations and concepts in SNOMED CT.

ABSTRACT:

Objective

Quality assurance of large ontological systems such as SNOMED CT is an indispensable part of the terminology management lifecycle. We introduce a hybrid structural-lexical method for scalable and systematic discovery of missing hierarchical relations and concepts in SNOMED CT.

Material and methods

All non-lattice subgraphs (the structural part) in SNOMED CT are exhaustively extracted using a scalable MapReduce algorithm. Four lexical patterns (the lexical part) are identified among the extracted non-lattice subgraphs. Non-lattice subgraphs exhibiting such lexical patterns are often indicative of missing hierarchical relations or concepts. Each lexical pattern is associated with a potential specific type of error.

Results

Applying the structural-lexical metho

SUBMITTER: Cui L 

PROVIDER: S-EPMC6080685 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature