Toward Robust Food Ontology Mapping

Author(s):  
Riste Stojanov ◽  
Ilija Kocev ◽  
Sasho Gramatikov ◽  
Gorjan Popovski ◽  
Barbara Korousic Seljak ◽  
...  
Keyword(s):  
Author(s):  
OkJoon Kim ◽  
Uma Jayaram ◽  
Sankar Jayaram ◽  
Lijuan Zhu

This paper presents our continuing work to develop methods to exchange product knowledge in the semantic level in the CAD/CAE domains. We present an approach based on a shared ontology, in which a higher level of ontologies are shared among lower levels of ontologies. Key mapping strategies, such as Equivalency, Attribute Similarity, Composition Similarity, and Inheritance Similarity are defined to map concepts and properties defined in a product design domain and an assembly simulation domain. In addition, a Bridge Ontology is designed to store information obtained from mapping processes and construct a link between different knowledge repositories. An Ontology Mapping Application (OMA) which brings together all these elements has been designed and implemented. It is a Java-based application that allows the user to load source and target ontologies, calculate concept and property similarities between them, display the mapping results, and output a corresponding Bridge Ontology.


2013 ◽  
Vol 748 ◽  
pp. 967-971
Author(s):  
Wei Gao ◽  
Tian Wei Xu ◽  
Li Liang ◽  
Jian Hou Gan

Ontology similarity calculation and ontology mapping are important research topics in information retrieval. One method for ontology similarity measure is using multi-dividing approach. Assume that the notation and terminology used but undefined in this paper can be found in [4] and [5]. We show that the assumption of strict ordering of xi*can be relaxed to allow some ties in the likelihood ratio. The same proof remains true if we consider equivalence classes defined by the likelihood ratio and relabel xi* as its equivalence class denoted by [xi*].


Sign in / Sign up

Export Citation Format

Share Document