This systematic literature review explores the application of artificial intelligence (AI) and machine learning (ML) in libraries. The objective of the study is to provide a synthesis of empirical studies in this area. The researchers conducted a systematic literature review based on established guidelines, collecting data from various databases including Web of Science, Scopus, LISA, and LISTA. After a rigorous selection process, 32 articles were selected for review and analysis. The findings reveal that the current state of AI and ML research in libraries mainly focuses on theoretical works, although some researchers also emphasize implementation projects or case studies. The study identifies the AI and ML techniques most often used in libraries and summarizes them in Table 2. These techniques include machine learning algorithms and artificial intelligence methods applied to different aspects of library operations. The inclusion criteria for articles in this review were that they must be written in English, discuss ML or AI applications, belong to the sub-area of Library and Information Science, and have titles, abstracts, and keywords related to libraries with the application of either machine learning or artificial intelligence. Exclusion criteria included non-digital publications, publications not available for full review, articles not in English language, and those without any application of ML or AI in libraries. The study selection process involved an initial screening based on title and abstract followed by assessment using the inclusion and exclusion criteria. A total of 379 articles were initially retrieved from various databases but after removing duplicates (16.09%), 286 papers remained. Finally, 32 articles were included in the systematic review. This study provides a panoramic view of AI and ML in libraries for researchers, practitioners, and educators interested in technology-oriented approaches. It highlights the need for further research and innovation pathways in this field. Overall, it contributes to the understanding of how cutting-edge technologies like AI and ML are being applied within library settings.
- Systematic literature review on the application of AI and ML in libraries
- Data collected from various databases including Web of Science, Scopus, LISA, and LISTA
- 32 articles selected for review and analysis
- Current state of AI and ML research in libraries focuses on theoretical works, implementation projects, and case studies
- Identified AI and ML techniques commonly used in libraries summarized in Table 2
- Inclusion criteria: English language, ML or AI applications, Library and Information Science sub-area with relevant titles, abstracts, and keywords
- Exclusion criteria: non-digital publications, unavailable for full review, non-English language without ML or AI applications in libraries
- Initial screening based on title and abstract followed by assessment using inclusion/exclusion criteria
- Panoramic view of AI and ML in libraries provided for researchers, practitioners, educators interested in technology-oriented approaches
- Highlights the need for further research and innovation pathways in this field
A group of people did a study on how artificial intelligence (AI) and machine learning (ML) are used in libraries. They looked at information from different databases like Web of Science, Scopus, LISA, and LISTA. They found 32 articles that they reviewed and analyzed. The current research on AI and ML in libraries focuses on theories, projects, and case studies. They made a list of the common techniques used in libraries with AI and ML. They only included articles that were in English and had to do with AI or ML in libraries. They didn't include articles that weren't digital or not available for review, or if they were in a language other than English without AI or ML in libraries. They first looked at the titles and summaries of the articles before deciding which ones to include or exclude. This study gives an overview of how AI and ML are used in libraries for researchers, librarians, teachers who are interested in technology approaches. It also shows that more research is needed in this area."
Definitions
- Systematic literature review: A careful study where people look at lots of different articles about a specific topic.
- Application: How something is used or put into practice.
- Artificial intelligence (AI): When computers can do things that normally need human thinking.
- Machine learning (ML): When computers can learn from data without being programmed directly.
- Databases: Places where lots of information is stored electronically.
- Review: Looking closely at something to understand it better.
Exploring the Application of Artificial Intelligence and Machine Learning in Libraries: A Systematic Literature Review
The use of artificial intelligence (AI) and machine learning (ML) has become increasingly popular in many industries, including libraries. AI and ML can be used to automate processes, improve efficiency, and provide more personalized services. This systematic literature review explores the application of AI and ML in libraries with the aim of providing a synthesis of empirical studies on this topic.
Methods
The researchers conducted a systematic literature review based on established guidelines, collecting data from various databases including Web of Science, Scopus, LISA, and LISTA. After a rigorous selection process involving an initial screening based on title and abstract followed by assessment using inclusion/exclusion criteria, 32 articles were selected for review and analysis. The inclusion criteria for articles included that they must be written in English; discuss ML or AI applications; belong to the sub-area of Library & Information Science; have titles, abstracts & keywords related to libraries with application either machine learning or artificial intelligence; while exclusion criteria included non-digital publications; publications not available for full review; articles not in English language; those without any application of ML or AI in libraries.
Findings
The findings reveal that current state research into AI & ML within library settings mainly focuses on theoretical works although some researchers also emphasize implementation projects or case studies. Table 2 summarizes the most commonly used techniques which include machine learning algorithms & artificial intelligence methods applied to different aspects such as library operations & services.
Conclusion
This study provides a panoramic view into how cutting-edge technologies like AI & ML are being applied within library settings for researchers, practitioners & educators interested in technology-oriented approaches. It highlights need further research & innovation pathways this field while contributing understanding how these technologies are currently being utilized within library settings
