Authors:
Wei Lin
;
Changjun Hu
;
Yang Li
and
Xin Cheng
Affiliation:
University of Science and Technology Beijing, China
Keyword(s):
Ontology, Mapping, Similarity Measure, Material Scientific Data.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Data Engineering
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Ontology and the Semantic Web
;
Society, e-Business and e-Government
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
Abstract:
How to accurately retrieve data for users from massive, distributed and relational complex material databases is a major challenge in the domain of material science. Ontology mapping is regarded as a solution provider to the problem addressed. The number of material ontologies that are publicly available and accessible increases dramatically, so does the need for establishing semantic mapping among them to ensure interoperability. In this paper, we proposed a compositive similarity measure for ontology mapping. The material ontologies are generated from relational databases schemas based on rules. Then they are compared from concept name, structure and individuals. Finally, we describe a set of experiments on material science domain and show that our method propose highly accurate ontology mapping.