Ontology Matching: State of the Art and Future Challenges

被引:559
|
作者
Shvaiko, Pavel [1 ]
Euzenat, Jerome [2 ,3 ]
机构
[1] Informat Trentina, TasLab, I-38121 Trento, Italy
[2] INRIA Grenoble Rhone Alpes, INRIA, F-38334 Montbonnot St Martin, France
[3] INRIA Grenoble Rhone Alpes, LIG, F-38334 Montbonnot St Martin, France
关键词
Semantic heterogeneity; semantic technologies; ontology matching; ontology alignment; schema matching; SEMANTIC-INTEGRATION; ALIGNMENT; FRAMEWORK; DATABASE; SCHEMAS; COMMUNITY; HETEROGENEITY; ALGORITHM; KNOWLEDGE; MAPPINGS;
D O I
10.1109/TKDE.2011.253
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
After years of research on ontology matching, it is reasonable to consider several questions: is the field of ontology matching still making progress? Is this progress significant enough to pursue further research? If so, what are the particularly promising directions? To answer these questions, we review the state of the art of ontology matching and analyze the results of recent ontology matching evaluations. These results show a measurable improvement in the field, the speed of which is albeit slowing down. We conjecture that significant improvements can be obtained only by addressing important challenges for ontology matching. We present such challenges with insights on how to approach them, thereby aiming to direct research into the most promising tracks and to facilitate the progress of the field.
引用
收藏
页码:158 / 176
页数:19
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