{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/130147"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/130147","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Disambiguating academic institution names: a comprehensive study of authority files, linguistic variations, and computational evaluation in PubMed affiliations","abstract":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01","abstract_html":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01","abstract_has_math":false,"creators":["Guan, Yingjun"],"institution":"University of Illinois Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Information Sciences","degree_department":null,"school":null,"contributors":["Torvik, Vetle I.","Torvik, Vetle I","Downie, Stephen","Ludäscher, Bertram","Renear, Allen"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-07-11","date_published":"2025-07-11","updated_at":"2026-07-22T22:25:06Z","subjects":["Natural Language Processing","Institution Name Disambiguation","Data Mining","Text Mining","Authority Control."],"languages":["en","eng"],"rights":["Copyright 2025 Yingjun Guan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/130147","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Torvik, Vetle I.","Torvik, Vetle I","Downie, Stephen","Ludäscher, Bertram","Renear, Allen"]},{"key":"dc:creator","label":"Author","values":["Guan, Yingjun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-07-11","2025-08"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Information Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Natural Language Processing","Institution Name Disambiguation","Data Mining","Text Mining","Authority Control."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Yingjun Guan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/130147"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01","The student, Yingjun Guan, accepted the attached license on 2025-07-10 at 12:03.","The student, Yingjun Guan, submitted this Dissertation for approval on 2025-07-10 at 12:07.","This Dissertation was approved for publication on 2025-07-11 at 15:18.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22431 on 2025-10-25 at 15:53:11","Accurate representation of academic institution names is critical for bibliometric analysis, scholarly communication, and digital library systems. However, variations in naming conventions, institutional hierarchies, and multilingual expressions pose significant challenges for consistent affiliation metadata. This dissertation shows a comprehensive investigation into Institution Name Disambiguation (IND), with a focus on authority files, linguistic analysis, and empirical evaluation using PubMed affiliation data. First, the study reviews the conceptual foundations of institutional name ambiguity and examines 21 prominent authority files, including VIAF, ROR, and Wikidata. A new integrated authority dataset is developed to enhance institutional name standardization. Second, we create a manually annotated dataset from real-world PubMed affiliation records to capture synonym patterns, structural inconsistencies, and user-written variations. Third, the dissertation evaluates both coverage of the authority files and the performance of computational tools for institutional name recognition and disambiguation across multiple metrics. Key contributions include a structured evaluation of authority file quality, benchmark datasets for institutional name analysis, InsVar and AffiNorm, and experimental insights into best practices for combining authority control with computational methods. The findings have broad implications for improving data integrity in academic publishing, digital knowledge infrastructures, and citation indexing systems."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Disambiguating academic institution names: a comprehensive study of authority files, linguistic variations, and computational evaluation in PubMed affiliations"]}]}],"canonical_facts":{"dc:contributor":["Torvik, Vetle I.","Torvik, Vetle I","Downie, Stephen","Ludäscher, Bertram","Renear, Allen"],"dc:creator":["Guan, Yingjun"],"dc:date":["2025-07-11","2025-08"],"dc:description":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01","The student, Yingjun Guan, accepted the attached license on 2025-07-10 at 12:03.","The student, Yingjun Guan, submitted this Dissertation for approval on 2025-07-10 at 12:07.","This Dissertation was approved for publication on 2025-07-11 at 15:18.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22431 on 2025-10-25 at 15:53:11","Accurate representation of academic institution names is critical for bibliometric analysis, scholarly communication, and digital library systems. However, variations in naming conventions, institutional hierarchies, and multilingual expressions pose significant challenges for consistent affiliation metadata. This dissertation shows a comprehensive investigation into Institution Name Disambiguation (IND), with a focus on authority files, linguistic analysis, and empirical evaluation using PubMed affiliation data. First, the study reviews the conceptual foundations of institutional name ambiguity and examines 21 prominent authority files, including VIAF, ROR, and Wikidata. A new integrated authority dataset is developed to enhance institutional name standardization. Second, we create a manually annotated dataset from real-world PubMed affiliation records to capture synonym patterns, structural inconsistencies, and user-written variations. Third, the dissertation evaluates both coverage of the authority files and the performance of computational tools for institutional name recognition and disambiguation across multiple metrics. Key contributions include a structured evaluation of authority file quality, benchmark datasets for institutional name analysis, InsVar and AffiNorm, and experimental insights into best practices for combining authority control with computational methods. The findings have broad implications for improving data integrity in academic publishing, digital knowledge infrastructures, and citation indexing systems."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/130147"],"dc:language":["en","eng"],"dc:rights":["Copyright 2025 Yingjun Guan"],"dc:subject":["Natural Language Processing","Institution Name Disambiguation","Data Mining","Text Mining","Authority Control."],"dc:title":["Disambiguating academic institution names: a comprehensive study of authority files, linguistic variations, and computational evaluation in PubMed affiliations"],"dc:type":["text"],"thesis:degree_discipline":["Information Sciences"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:06Z"}