Konuşmacılar
Açıklama
Successfully providing personalized book recommendations is crucial for platforms. The power law concept highlights that a small number of individuals have a large number of connections, which leads to the "Power of Few" principle. To enhance the accuracy of book recommendations, a new approach that integrates Social Network Analysis (SNA) with recommender systems can be proposed. By identifying influential users within a social network and utilizing their preferences, recommendation systems can be improved. A network composed of user interactions and book ratings can be constructed to identify these influential users. The preferences of these users can then be analyzed using the recommendation system. It is anticipated that a small number of influential users will significantly increase the accuracy of recommendations. This method investigates the importance of network dynamics in recommendation systems and aims to provide more satisfying book recommendations.
Institution / Affiliation / Kurum
İstanbul Üniversitesi
Presentation language / Sunum Dili | TR (Türkçe) |
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Disciplines / Disiplinler | Literary studies / Edebiyat Bilimi |
E-mail / E-posta | sebnemakal@marmara.edu.tr |
ORCID ID | 0000-0001-8239-2957 |
Country / Ülke | Türkiye |