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KLD is effective in the relation predicate extraction, and MI can extract the reciprocity between semantic type and predicate.
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Since MI can measure the reciprocity between semantic types and relation predicates, it is applied in our study to filter out the semantic types and relation predicates.
In order to cover linguistic generalizations, it is proposed to relax the relation between an expression and its semantic type (and therefore with its meaning).
We model a biomedical literature as a concept network G, where each node represents a biomedical concept that belongs to certain semantic type, and each edge represents a relationship between two concepts.
In this work, we consider the following two types of semantic information for a given node, its semantic type and its related author information.
Objects are grouped under syntactic and semantic types, and interesting differences between kinds of representational system track differences in the way syntactic and semantic types relate to one another.
A specific pattern, called prime category, was created for every semantic category resulting in 23 categories for the UMLS semantic types and 4 categories for the Edam types.
Then, depending on such semantic types and cardinalities, we defined the possible semantic types of the biologically meaningful biomolecular annotations that can be transferred by transitive relationship.
We classify diseases according to UMLS semantic types and MeSH classes.
The KM method completes the extraction of entity semantic types and relation predicates.
Cimino et al. (2003) used mismatches between the semantic types of parent and child nodes linked via the IS-A relation to uncover inconsistencies in the UMLS Metathesaurus.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com