Using Background Knowledge to Enhance Ontology Matching: a Survey

Tracking #: 1525-2737

This paper is currently under review
Clement Jonquet

Responsible editor: 
Jérôme Euzenat

Submission type: 
Survey Article
The ontology matching research community has been very active since a decade. Recently proposed state-of-the-art approaches promote the use of external resources or previously discovered mappings as a Background Knowledge (BK) for enhancing the ontology matching quality. Several important questions related to the use of a BK arise: (i) in which cases the use of the background knowledge is justified and necessary ? and (ii) what is the tradeoff between the complexity of the alignment methods and the background knowledge in terms of the quality of matching and time execution? Another interesting issue is the selection of the most useful BK for a given ontology alignment task. In this paper, we review the different approaches in respect to the kind of background knowledge used and implemented ontology matching techniques and provide a synthetic classification of these approaches. Furthermore, we address the problem of BK selection by providing a review of existing methods. Finally, we provide a comparative experimental review of BK-based alignment systems by analyzing their performance results obtained during Ontology Alignment Evaluation Initiative (OAEI) 2012-2016 campaigns. We thus evaluate the benefit of using a BK and the improvement achieved by these approaches regarding to the systems that do not use a BK.
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