Paper Info
Title
Ontology Matching using Multiple Similarity Measures.
Abstract
This paper presents an automatic ontology matching approach (called LSSOM - Lexical Structural Semantic-based Ontology Matching method) which brings a final alignment by combining three kinds of different similarity measures: lexical-based, structure-based, and semantic-based techniques as well as using information in ontologies including names, labels, comments, relations and positions of concepts in the hierarchy and integrating WordNet dictionary. Firstly, two ontologies are matched sequentially by using the lexical-based and structure-based similarity measures to find structural correspondences among the concepts. Secondly, the semantic similarity based on WordNet dictionary is applied to these concepts in given ontologies. After the semantic and structural similarities are obtained, they are combined in the parallel phase by using weighted sum method to yield the final similarities. Our system is implemented and evaluated based on the OAEI 2008 benchmark dataset. The experimental results show that our approach obtains good F-measure values and outperforms other automatic ontology matching systems which do not use instances information.
Year
DOI
Venue
2015
10.5220/0005615606030611
KDIR
Keywords
Field
DocType
Ontology Matching, Lexical, Structure, Semantic
Ontology (information science),Semantic similarity,Ontology alignment,Ontology-based data integration,Data mining,Information retrieval,Computer science,WordNet,Upper ontology,Hierarchy
Conference
Citations 
PageRank 
References 
3
0.40
0
Authors
2
Name
Order
Citations
PageRank
Thi Thuy Anh Nguyen151.80
Stefan Conrad 0001272.53