Jaeho Lee, Younhee Kim, Hyunkyung Shin, Kibong Song, Journal of Internet Computing and Services, Vol. 15, No. 3, pp. 125-0, Jun. 2014
10.7472/jksii.2014.15.3.125, Full Text:
Keywords: Alzheimer disease, Ontology, knowledge representation, database of domestic academic papers, inference based query

Abstract

In the medical field, for the purpose of diagnosis and treatment of diseases, building knowledge base has received a lot of attention. The most important thing to build a knowledge base is representing the knowledge accurately. In this paper we suggest a knowledge representation method using Ontology technique with the datasets obtained from the domestic papers on Alzheimer disease that has received a lot of attention recently in the medical field. The suggested Ontology for Alzheimer disease defines all the possible classes: lexical information from journals such as 'author' and 'publisher' research subjects extracted from 'title', 'abstract', 'keywords', and 'results'. It also included various semantic relationships between classes through the Ontology properties. Inference can be supported since our Ontology adopts hierarchical tree structure for the classes and transitional characteristics of the properties. Therefore, semantic representation based query is allowed as well as simple keyword query, which enables inference based knowledge query using an Ontology query language 'SPARQL'.

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