Track: Type A (Regular Papers)
Keywords: Multiple-carousel recommendation systems, Recommendation system evaluation, Book Recommendation, Recommendation systems
Abstract: Using multiple carousels, lists that wrap around and can be scrolled, is the basis for offering content in most contemporary movie
streaming platforms. Carousels allow for highlighting different aspects of users' taste, that fall in categories such as genres and authors. However, while carousels offer structure and greater ease of navigation, they alone do not increase diversity in recommendations, while this is essential to keep users engaged. In this work we propose several approaches to effectively increase item diversity within the domain of book recommendations, on top of a collaborative filtering algorithm. These approaches are intended to improve book recommendations in the web catalogs of public libraries. Furthermore, we introduce metrics to evaluate the resulting strategies, and show that the proposed system finds a suitable balance between accuracy and beyond-accuracy aspects.
Serve As Reviewer: ~Gideon_Maillette_de_Buy_Wenniger1
Submission Number: 20
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