User Control in Recommender Systems: Overview and Interaction Challenges

Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 278)

Abstract

Recommender systems have shown to be valuable tools that help users find items of interest in situations of information overload. These systems usually predict the relevance of each item for the individual user based on their past preferences and their observed behavior. If the system’s assumption about the users’ preferences are however incorrect or outdated, mechanisms should be provided that put the user into control of the recommendations, e.g., by letting them specify their preferences explicitly or by allowing them to give feedback on the recommendations. In this paper we review and classify the different approaches from the research literature of putting the users into active control of what is recommended. We highlight the challenges related to the design of the corresponding user interaction mechanisms and finally present the results of a survey-based study in which we gathered user feedback on the implemented user control features on Amazon.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Dietmar Jannach
    • 1
  • Sidra Naveed
    • 1
  • Michael Jugovac
    • 1
  1. 1.Department of Computer ScienceTU DortmundDortmundGermany

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