Boosting Biomedical Entity Extraction by Using Syntactic Patterns for Semantic Relation Discovery

Biomedical entity extraction from unstructured web documents is an important task that needs to be performed in order to discover knowledge in the veterinary medicine domain. In general, this task can be approached by applying domainspecific ontologies, but a review of the literature shows that there is no universal dictionary, or ontology for this domain. To address this issue, we manually construct an ontology for extracting entities such as: animal disease names, viruses and serotypes. We then use an automated ontology expansion approach to extract semantic relationships between concepts. Such relationships include asserted synonymy, hyponymy and causality. Specifically, these relationships are extracted by using a set of syntactic patterns and part-of-speech tagging. The resulting ontology contains richer semantics compared to the manuallyconstructed ontology. We compare our approach for extracting synonyms, hyponyms and other disease related concepts, with an approach where the on...

• Type: Journal
• Year: 2010
• Where: WEBI
• Authors: Svitlana Volkova, Doina Caragea, William H. Hsu, John Drouhard, Landon Fowles
• Keywords: Entity Extraction, Internet Technology, Ontology, Semantic Relationship, WEBI 2010