Towards evaluating complex ontology alignments. (2020)

• Record Type: Journal Article
• Authors: Zhou, Lu; Thiéblin, Elodie; Cheatham, Michelle; Faria, Daniel; Pesquita, Catia; Trojahn, Cassia; Zamazal, Ondřej
• Is Part Of: Knowledge engineering review. Volume 35(2020)
• Publication Date: 2020
• Subjects: Expert systems (Computer science) -- Periodicals; 006.33
• DOI: 10.1017/S0269888920000168
• Languages: English
• ISSNs: 0269-8889

Abstract

Abstract: The development of semi-automated and automated ontology alignment techniques is an important part of realizing the potential of the Semantic Web. Until very recently, most existing work in this area was focused on finding simple (1:1) equivalence correspondences between two ontologies. However, many real-world ontology pairs involve correspondences that contain multiple entities from each ontology. These 'complex' alignments pose a challenge for existing evaluation approaches, which hinders the development of new systems capable of finding such correspondences. This position paper surveys and analyzes the requirements for effective evaluation of complex ontology alignments and assesses the degree to which these requirements are met by existing approaches. It also provides a roadmap for future work on this topic taking into consideration emerging community initiatives and major challenges that need to be addressed.