AgreementMakerLight

IF 3 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Semantic Web Pub Date : 2023-06-22 DOI:10.3233/sw-233304

Daniel Faria, Emanuel Santos, B. Balasubramani, M. C. Silva, Francisco M. Couto, Catia Pesquita

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引用次数: 0

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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AgreementMakerLight

本体匹配在相关本体的实体之间建立对应关系，其应用范围从启用语义互操作性到支持本体和知识图开发。随着支持信息系统或人工智能应用程序的知识图的普及，语义Web社区对它的需求正在上升。在本文中，我们展示了AgreementMakerLight (AML)，一个自2013年以来不断开发的本体匹配系统，在九个版本的本体校准评估计划(OAEI)中展示了性能，以及跨各种领域的实际应用历史。我们概述了AML的架构和算法、用户界面和功能、性能及其影响。自2013年以来，AML参与的OAEI曲目比其他任何匹配系统都多，自2014年以来，每年所有曲目的F-measure排名中位数在1到2之间，运行时间排名在3到4之间。因此，它提供了范围，质量和效率的组合，很少有匹配系统可以竞争。此外，“反洗钱”的影响可以通过引用一篇或多篇论文的263篇(非自我)出版物来衡量，其中我们统计了34篇实际应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

8.30

自引率

6.70%

发文量

期刊介绍： The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.