000162403 001__ 162403
000162403 005__ 20251017144601.0
000162403 0247_ $$2doi$$a10.1007/s11192-025-05368-1
000162403 0248_ $$2sideral$$a144988
000162403 037__ $$aART-2025-144988
000162403 041__ $$aeng
000162403 100__ $$0(orcid)0009-0000-9128-1394$$aMuñoz-Jordán, David
000162403 245__ $$a3SA: an entity-linking algorithm for the Institution Name Disambiguation problem in affiliations using edit distance
000162403 260__ $$c2025
000162403 5060_ $$aAccess copy available to the general public$$fUnrestricted
000162403 5203_ $$aWhen researchers sign an article, they reference all the institutions they belong to, writing one or more affiliations containing them. Researchers sign in many different ways, and different journals also have varying standards in this regard. In this article we will focus on the Institution Name Disambiguation (IND) problem, also known as Organization Name Disambiguation (OND). Common issues associated to IND problem arise because researchers may write the name of the institution differently in various publications, and different researchers from the same institution will certainly write it differently as well. On the other hand, a researcher may be affiliated with several centers simultaneously or at different stages of their professional life, which introduces the factor of time as an additional variable to consider. As a result, analyzing and linking scientific work from different areas for various institutions is challenging. Databases like Web of Science collect articles from various journals across different fields. In this article, we will propose a method named 3 Steps Affiliation (3SA) based on, firstly, preprocessing the information, secondly, candidate extraction via localization and classification type of the institutions and, thirdly, on entity linking to extract the institutions from affiliations downloaded from Web of Science articles using an edit distance. We use a world-wide open source database with more than 100k institutions to solve the Institution Name Disambiguation problem. We show that the proposed method has a state-of-art performance by comparing it with other methods. Additionally, we evaluate the impact of different edit distance metrics within our method to identify which yields the best results.
000162403 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E30-23R$$9info:eu-repo/grantAgreement/ES/MICINN AEI/PID2022-136374NB-C22
000162403 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000162403 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000162403 700__ $$0(orcid)0000-0002-0342-0225$$aRuiz, Gonzalo
000162403 700__ $$aCabriada, Pablo
000162403 700__ $$aDurán, Juan Luis
000162403 700__ $$aIñiguez, David
000162403 700__ $$0(orcid)0000-0002-6689-214X$$aRivero, Alejandro
000162403 773__ $$g(2025), [19 pp.]$$pScientometrics$$tSCIENTOMETRICS$$x0138-9130
000162403 8564_ $$s901488$$uhttps://zaguan.unizar.es/record/162403/files/texto_completo.pdf$$yVersión publicada
000162403 8564_ $$s1629145$$uhttps://zaguan.unizar.es/record/162403/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000162403 909CO $$ooai:zaguan.unizar.es:162403$$particulos$$pdriver
000162403 951__ $$a2025-10-17-14:14:12
000162403 980__ $$aARTICLE