Loepp, Benedikt:
Multi-list interfaces for recommender systems : Survey and future directions
In: Frontiers in Big Data, Band 6 (2023), Artikel 1239705
2023Artikel/Aufsatz in ZeitschriftOA Gold
InformatikFakultät für Ingenieurwissenschaften » Informatik und Angewandte Kognitionswissenschaft » Informatik » Interaktive Systeme / Interaktionsdesign
Damit verbunden: 1 Publikation(en)
Titel in Englisch:
Multi-list interfaces for recommender systems : Survey and future directions
Loepp, BenediktUDE
0000-0001-9059-5324ORCID iD
der Hochschule zugeordnete*r Autor*in
korrespondierende*r Autor*in
Open Access?:
OA Gold
DuEPublico 2 ID
Web of Science ID
PubMed ID
Scopus ID
OA Förderung 2023
Sprache des Textes:
Schlagwort, Thema:
Recommender systems ; Multi-list recommendation ; Carousels ; User interfaces ; User experience ; Choice overload ; Survey

Abstract in Englisch:

For a long time, recommender systems presented their results in the form of simple item lists. In recent years, however, multi-list interfaces have become the de-facto standard in industry, presenting users with numerous collections of recommendations, one below the other, each containing items with common characteristics. Netflix's interface, for instance, shows movies from certain genres, new releases, and lists of curated content. Spotify recommends new songs and albums, podcasts on specific topics, and what similar users are listening to. Despite their popularity, research on these so-called “carousels” is still limited. Few authors have investigated how to simulate the user behavior and how to optimize the recommendation process accordingly. The number of studies involving users is even smaller, with sometimes conflicting results. Consequently, little is known about how to design carousel-based interfaces for achieving the best user experience. This mini review aims to organize the existing knowledge and outlines directions that may improve the multi-list presentation of recommendations in the future.