Large Scale Ontology Matching System (LSMatch)

被引:0
|
作者
Sharma A. [1 ]
Jain S. [1 ]
Patel A. [2 ]
机构
[1] Department of Computer Applications, National Institute of Technology, Kurukshetra
[2] School of Law, Forensic Justice and Policy Studies, National Forensic Sciences University, Gujarat, Gandhinagar
关键词
knowledge graph; LSMatch; Ontology; ontology alignment; ontology matching parameters; ontology matching systems;
D O I
10.2174/2666255816666230606140526
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Background: Ontology matching provides a solution to the semantic heterogeneity problem by finding semantic relationships between entities of ontologies. Over the last two decades, there has been considerable development and improvement in the ontology matching paradigm. More than 50 ontology matching systems have been developed, and some of them are performing really well. However, the initial rate of improvement was measurably high, which now is slowing down. However, there still is room for improvement, which we as a community can work towards to achieve. Method: In this light, we have developed a Large Scale Ontology Matching System (LSMatch), which uses different matchers to find similarities between concepts of two ontologies. LSMatch mainly uses two modules for matching. These modules perform string similarity and synonyms matching on the concepts of the ontologies. Results: For the evaluation of LSMatch, we have tested it in Ontology Alignment Evaluation Initiative (OAEI) 2021. The performance results show that LSMatch can perform matching operations on large ontologies. LSMatch was evaluated on anatomy, disease and phenotype, conference, Knowledge graph, and Common Knowledge Graphs (KG) track. In all of these tracks, LSMatch’s performance was at par with other systems. Conclusion: Being LSMatch’s first participation, the system showed potential and has room for improvement. © 2024 Bentham Science Publishers.
引用
收藏
页码:20 / 30
页数:10
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