Bibliometric Analysis of Recommender Systems Literature

Year 2024, Volume: 12 Issue: 3, 232 - 251, 31.12.2024

Can İlkhan , Emrah Önder

https://doi.org/10.22139/jobs.1476377

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.

Keywords

Recommender Systems, Bibliometric Analysis, Citation Analysis, Vosviewer

Tavsiye Sistemleri Literatürünün Bibliyometrik Analizi

Abstract

Bu çalışma, tavsiye sistemleri literatürünün son beş yılda gerçekleştirilen bibliyometrik analizini içermektedir. Web of Science (WoS) veri tabanından elde edilen veriler kullanılarak, bu alanın gelişimi ve dönemeç noktaları detaylı bir şekilde incelenmiştir. Tavsiye sistemleri, kullanıcı verilerini kullanarak kişiselleştirilmiş içerik ve ürün önerileri sunan teknolojilerdir ve bu sistemler, internetin ve dijital işlemlerin yaygınlaşmasıyla birlikte önem kazanmıştır. Kullanıcılar tarafından verilen doğrudan geri bildirimler veya göz izleme teknolojisi gibi yöntemlerle elde edilen zengin veriler, kullanıcı tercihlerinin analiz edilmesi ve ihtiyaçlara uygun önerilerin sunulması için kullanılmaktadır. Araştırma, GroupLens çalışması gibi önemli adımları ele alarak, işbirlikçi filtreleme ve içerik tabanlı filtreleme gibi temel yaklaşımların gelişimine ışık tutmaktadır. Bu sistemler, Google ve Facebook gibi platformlar tarafından kullanıcı etkileşimlerini analiz edip, gelecekteki tercihleri tahmin etmek amacıyla kullanılmaktadır. Bibliyometrik analiz, VOSviewer aracılığıyla yapılan görselleştirmelerle desteklenmiş olup, tavsiye sistemleri literatüründe sıkça karşılaşılan terimlerin ve bu terimler arasındaki ilişkilerin detaylı bir haritasını sunmaktadır. Çalışma, bu alanda araştırma yapacak olanlara rehberlik edecek şekilde tasarlanmıştır ve tavsiye sistemlerinin bilimsel etkisinin arttığını göstermektedir. Bibliyometrik analiz, bilimsel yayınların niceliksel bir değerlendirmesini sağlayarak, bu yayınların bilimsel etki ve kalitesini objektif bir şekilde ölçmüştür. Analiz sonuçları, tavsiye sistemleri alanındaki akademik çalışmaların ve atıfların zaman içindeki artışını göstermektedir ve bu artış, alandaki ilginin ve etkinin giderek arttığını işaret etmektedir. Bu tür bir analiz, gelecekte bu konu üzerine çalışacak araştırmacılara yol gösterici olabilir ve tavsiye sistemlerinin daha da geliştirilmesi için temel oluşturabilir. Sonuç olarak, bu çalışma, tavsiye sistemleri literatürünün kapsamlı bir analizini sunmakta ve araştırma alanındaki bilimsel ilerlemeleri daha derinlemesine inceleme imkanı sağlamaktadır.

Keywords

Tavsiye Sistemleri, Bibliyometrik Analiz, Atıf Analizi, Vosviewer

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