Tavsiye Sistemleri Literatürünün Bibliyometrik Analizi
Bibliometric Analysis of Recommender Systems Literature
Author(s): Can İlkhan, Emrah ÖnderSubject(s): Business Economy / Management, ICT Information and Communications Technologies, Socio-Economic Research
Published by: Sakarya üniversitesi
Keywords: Recommender Systems; Bibliometric Analysis; Citation Analysis; Vosviewer;
Summary/Abstract: This study includes a bibliometric analysis of the literature on recommendation systems conducted over the past five years. Utilizing data obtained from the Web of Science (WoS) database, this research meticulously examines this field's development and turning points. Recommendation systems, which offer personalized content and product suggestions using user data, have gained significance with the widespread adoption of the internet and digital transactions. Rich data gathered through direct user feedback or methods such as eye-tracking technology are used to analyze user preferences and provide suitable recommendations. The research addresses significant milestones such as the GroupLens study, shedding light on the development of fundamental approaches like collaborative filtering and content-based filtering. Platforms like Google and Facebook employ these systems to analyze user interactions and predict future preferences. The bibliometric analysis, supported by visualizations created with VOSviewer, presents a detailed map of the frequently encountered terms in the recommendation systems literature and the relationships between these terms. Designed to guide those researching in this area, the study demonstrates the increasing scientific impact of recommendation systems. Bibliometric analysis provides a quantitative assessment of scientific publications, objectively measuring their scientific impact and quality. The analysis results show an increase over time in academic studies and citations within the field of recommendation systems, indicating a growing interest and influence in the area. Such an analysis can serve as a guide for future researchers on this topic and lay the groundwork for further development of recommendation systems. In conclusion, this work offers a comprehensive analysis of the recommendation systems literature, allowing for a deeper examination of scientific advancements in the research field.
Journal: İşletme Bilimi Dergisi
- Issue Year: 12/2024
- Issue No: 3
- Page Range: 232-251
- Page Count: 20
- Language: Turkish
