本体对齐
本体论
计算机科学
匹配(统计)
开放生物医学本体论
情报检索
上层本体
图形
基于本体的数据集成
字符串搜索算法
语义异质性
语义相似性
语义网
人工智能
模式匹配
理论计算机科学
数学
哲学
统计
认识论
作者
Abhisek Sharma,Sarika Jain,Archana Patel
标识
DOI:10.2174/2666255816666230606140526
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.
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