AgreementMakerLight

Tracking #: 3304-4518

Authors: 
Daniel Faria
Emanuel Santos1
Booma Sowkarthiga Balasubramani
Marta Contreiras Silva
Francisco Moreira Couto
Catia Pesquita

Responsible editor: 
Guest Editors Tools Systems 2022

Submission type: 
Tool/System Report
Abstract: 
Ontology matching establishes correspondences between entities of related ontologies, with applications ranging from enabling semantic interoperability to supporting ontology and knowledge graph development. Its demand within the Semantic Web community is on the rise, as the popularity of knowledge graph supporting information systems or artificial intelligence applications continues to increase. In this article, we showcase AgreementMakerLight (AML), an ontology matching system in continuous development since 2013, with demonstrated performance over nine editions of the Ontology Alignment Evaluation Initiative (OAEI), and a history of real-world applications across a variety of domains. We overview AML's architecture and algorithms, its user interfaces and functionalities, its performance, and its impact. AML has participated in more OAEI tracks since 2013 than any other matching system, has a median rank by F-measure between 1 and 2 across all tracks in every year since 2014, and a rank by run time between 3 and 4. Thus, it offers a combination of range, quality and efficiency that few matching systems can rival. Moreover, AML's impact can be gauged by the 263 (non-self) publications that cite one or more of its papers, among which we count 34 real-world applications.
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Reviewed

Decision/Status: 
Accept

Solicited Reviews:
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Review #1
By Elodie Thieblin submitted on 07/Dec/2022
Suggestion:
Accept
Review Comment:

Thanks for taking my comments into account. I agree with the publication of this paper.

Review #2
Anonymous submitted on 21/Dec/2022
Suggestion:
Accept
Review Comment:

The authors have carefully addressed the comments and suggestions raised by the three reviewers. The paper now is in shape for publication, according to the constraints of this special issue.

Review #3
By Pavel Shvaiko submitted on 30/Dec/2022
Suggestion:
Accept
Review Comment:

The shortcomings identified in the previous round were adequately addressed. The revised submission has reached the due quality and is ready for publication.