Title :
Semantic enrichment in similarity combination for ontology
Author :
Kuan-Hao Huang ; Liu, Alan ; Jhih-Jhao Wang
Author_Institution :
Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan
Abstract :
Ontology can be seen as a knowledge sharing tool to communicate between different fields of knowledge. Each expert has their own way to design their ontologies using their own structures. This introduces a challenging problem of how to establish communication channels between these diversities. Ontology mapping is a good method to solve these problems by building relations between these ontologies. The core of ontology mapping is to compute the similarities between these concept pairs. In early years, researchers considered only single similarity for their ontology mapping. Recently, the scale of ontology has become more complicated. More researchers try to filter out all the possible similarities to combine concepts together to get a better result of mapping. One of the important similarity is the semantic similarity. In semantic similarity, how to get the attributes or properties to improve the scope of searching is an important part. This paper presents a method to improve the system by enriching the semantic similarity to expand the scope of the searching area. Constituting semantic similarity with other relations make the system have a better result in finding the correct similarity combinations and produce high possibility of successful mapping.
Keywords :
ontologies (artificial intelligence); semantic networks; knowledge sharing tool; ontology mapping; semantic enrichment; semantic similarity; similarity combination; Benchmark testing; Electrical engineering; Filtering; Mathematical model; Ontologies; Semantics; Speech; Ontology; Ontology Mapping; Semantic Enrichment; Similarity combination;
Conference_Titel :
Automatic Control Conference (CACS), 2014 CACS International
Print_ISBN :
978-1-4799-4586-3
DOI :
10.1109/CACS.2014.7097193