Advancing library operations with AI: data-driven insights for academic resource management
Introduction. The rapid evolution of artificial intelligence technologies affords opportunities and challenges for libraries. The study analyses the application of artificial intelligence tools for business intelligence purposes in a university library. Method. This study used artificial neural...
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| Format: | Article |
| Language: | English |
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University of Borås
2025-05-01
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| Series: | Information Research: An International Electronic Journal |
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| Online Access: | https://publicera.kb.se/ir/article/view/52261 |
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| author | Néstor A. Nova Hernán Morales Juan Pájaro Andrea González |
| author_facet | Néstor A. Nova Hernán Morales Juan Pájaro Andrea González |
| author_sort | Néstor A. Nova |
| collection | DOAJ |
| description |
Introduction. The rapid evolution of artificial intelligence technologies affords opportunities and challenges for libraries. The study analyses the application of artificial intelligence tools for business intelligence purposes in a university library.
Method. This study used artificial neural networks to extract metadata from a syllabus corpus and then applied a string-matching model to integrate the extracted data with the loan library database. Finally clustering algorithms were employed to analyse the results, providing valuable insights into resource usage patterns. Data was extracted from faculty databases from one university in Colombia.
Results. This study identified the potential of integrating artificial intelligence with business intelligence tools to enhance resource management and optimise university library operations, facilitating a better alignment between academic syllabi and available materials.
Conclusions. The study found that artificial intelligence tools are valuable for university libraries in optimising processes based on data analysis. This suggests that libraries should design and implement business intelligence initiatives to automate manual tasks, providing valuable information to managers and academic directors for decision-making in administrative and academic contexts.
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| format | Article |
| id | doaj-art-a82a38d0e5164ff5aef612e7a3fc25f8 |
| institution | OA Journals |
| issn | 1368-1613 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | University of Borås |
| record_format | Article |
| series | Information Research: An International Electronic Journal |
| spelling | doaj-art-a82a38d0e5164ff5aef612e7a3fc25f82025-08-20T02:32:22ZengUniversity of BoråsInformation Research: An International Electronic Journal1368-16132025-05-0130CoLIS10.47989/ir30CoLIS52261Advancing library operations with AI: data-driven insights for academic resource managementNéstor A. Nova0Hernán Morales1Juan Pájaro2Andrea González3Department of Information Science at Pontificia Universidad JaverianaDepartment of Information Science at Pontificia Universidad JaverianaDepartment of Clinical Epidemiology and Biostatistics at Pontificia Universidad JaverianaDepartment of Information Science at Pontificia Universidad Javeriana Introduction. The rapid evolution of artificial intelligence technologies affords opportunities and challenges for libraries. The study analyses the application of artificial intelligence tools for business intelligence purposes in a university library. Method. This study used artificial neural networks to extract metadata from a syllabus corpus and then applied a string-matching model to integrate the extracted data with the loan library database. Finally clustering algorithms were employed to analyse the results, providing valuable insights into resource usage patterns. Data was extracted from faculty databases from one university in Colombia. Results. This study identified the potential of integrating artificial intelligence with business intelligence tools to enhance resource management and optimise university library operations, facilitating a better alignment between academic syllabi and available materials. Conclusions. The study found that artificial intelligence tools are valuable for university libraries in optimising processes based on data analysis. This suggests that libraries should design and implement business intelligence initiatives to automate manual tasks, providing valuable information to managers and academic directors for decision-making in administrative and academic contexts. https://publicera.kb.se/ir/article/view/52261Artificial Intelligence in LIS, including ethical aspectsLibrary OperationsArtificial IntelligenceBusiness IntelligenceAcademic ManagementDecision Making |
| spellingShingle | Néstor A. Nova Hernán Morales Juan Pájaro Andrea González Advancing library operations with AI: data-driven insights for academic resource management Information Research: An International Electronic Journal Artificial Intelligence in LIS, including ethical aspects Library Operations Artificial Intelligence Business Intelligence Academic Management Decision Making |
| title | Advancing library operations with AI: data-driven insights for academic resource management |
| title_full | Advancing library operations with AI: data-driven insights for academic resource management |
| title_fullStr | Advancing library operations with AI: data-driven insights for academic resource management |
| title_full_unstemmed | Advancing library operations with AI: data-driven insights for academic resource management |
| title_short | Advancing library operations with AI: data-driven insights for academic resource management |
| title_sort | advancing library operations with ai data driven insights for academic resource management |
| topic | Artificial Intelligence in LIS, including ethical aspects Library Operations Artificial Intelligence Business Intelligence Academic Management Decision Making |
| url | https://publicera.kb.se/ir/article/view/52261 |
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