Towards psychology-aware preference construction in recommender systems: Overview and research issues

Müslüm Atas, Alexander Felfernig*, Seda Polat-Erdeniz, Andrei Popescu, Thi Ngoc Trang Tran, Mathias Uta

*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in einer FachzeitschriftArtikelBegutachtung


User preferences are a crucial input needed by recommender systems to determine relevant items. In single-shot recommendation scenarios such as content-based filtering and collaborative filtering, user preferences are represented, for example, as keywords, categories, and item ratings. In conversational recommendation approaches such as constraint-based and critiquing-based recommendation, user preferences are often represented on the semantic level in terms of item attribute values and critiques. In this article, we provide an overview of preference representations used in different types of recommender systems. In this context, we take into account the fact that preferences aren’t stable but are rather constructed within the scope of a recommendation process. In which way preferences are determined and adapted is influenced by various factors such as personality traits, emotional states, and cognitive biases. We summarize preference construction related research and also discuss aspects of counteracting cognitive biases.
Seiten (von - bis)467-489
FachzeitschriftJournal of Intelligent Information Systems
Frühes Online-Datum2021
PublikationsstatusVeröffentlicht - Dez. 2021

ASJC Scopus subject areas

  • Software
  • Artificial intelligence
  • Information systems
  • Hardware und Architektur
  • Computernetzwerke und -kommunikation

Dieses zitieren