Considering temporal aspects in recommender systems: a survey

Veronika Bogina, Tsvi Kuflik, Dietmar Jannach, Maria Bielikova, Michal Kompan, Christoph Trattner

Research output: Contribution to journalArticlepeer-review

Abstract

The widespread use of temporal aspects in user modeling indicates their importance, and their consideration showed to be highly effective in various domains related to user modeling, especially in recommender systems. Still, past and ongoing research, spread over several decades, provided multiple ad-hoc solutions, but no common understanding of the issue. There is no standardization and there is often little commonality in considering temporal aspects in different applications. This may ultimately lead to the problem that application developers define ad-hoc solutions for their problems at hand, sometimes missing or neglecting aspects that proved to be effective in similar cases. Therefore, a comprehensive survey of the consideration of temporal aspects in recommender systems is required. In this work, we provide an overview of various time-related aspects, categorize existing research, present a temporal abstraction and point to gaps that require future research. We anticipate this survey will become a reference point for researchers and practitioners alike when considering the potential application of temporal aspects in their personalized applications.

Original languageEnglish
JournalUser Modeling and User-Adapted Interaction
DOIs
StateAccepted/In press - 2022

Bibliographical note

Funding Information:
This study was partially supported by the Israeli Science Foundation (ISF) Grant Number 262/2017. This work was also partly supported by industry partners and the Research Council of Norway with funding to MediaFutures: Research Centre for Responsible Media Technology and Innovation, through the centers for Research-based Innovation scheme, Project Number 309339.

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature B.V.

Keywords

  • Dynamics
  • Long-term preferences
  • Recommender systems
  • Short-term preferences
  • Survey
  • Temporal aspects
  • User modeling

ASJC Scopus subject areas

  • Education
  • Human-Computer Interaction
  • Computer Science Applications

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