A lexical metaschema for the UMLS semantic network

Li Zhang, Yehoshua Perl, Michael Halper, James Geller, George Hripcsak
2005 Artificial Intelligence in Medicine  
Objective: A metaschema is a high-level abstraction network of the UMLS's Semantic Network (SN) obtained from a partition of the SN's collection of semantic types. Every metaschema has nodes, called meta-semantic types, each of which denotes a group of semantic types constituting a subject area of the SN. A new kind of metaschema, called the lexical metaschema, is derived from a lexical partition of the SN. The lexical metaschema is compared to previously derived metaschemas, e.g., the cohesive
more » ... metaschema. Design: A new lexical partitioning methodology is presented based on identical word-usage among the names of semantic types and the definitions of their respective children. The lexical metaschema is derived from the application of the methodology. We compare the constituent meta-semantic types and their underlying semantic-type groups with the previously derived cohesive metaschema. A similar comparison of the lexical partition and a published partition of the SN is also carried out. Results: The lexical partition of the SN has 21 semantic-type groups, each of which represents a subject area. The lexical metaschema thus has 21 meta-semantic types, 19 meta-child-of hierarchical relationships, and 86 meta-relationships. Our comparison shows that 15 out of the 21 meta-semantic types in the lexical metaschema also appear in the cohesive metaschema, and 80 semantic types are covered by identical meta-semantic types or refinements between the two metaschemas. The comparison between the lexical partition and the semantic partition shows that they have very low similarity. Conclusion: The algorithmically derived lexical metaschema serves as an abstraction of the SN 2 and provides views representing different subject areas. It compares favorably with the cohesive metaschema derived via the SN's relationship configuration.
doi:10.1016/j.artmed.2004.06.002 pmid:15617981 fatcat:cfm2s5qi4nd73exhsncrzpqnvu