Overview

This workshop is focusing on the aspect of integrating different theories of human decision making into the construction of recommender systems.

Topics of interest include but are not limited to:

  • Theories, algorithms and applications
    • Decision theories in recommender systems (e.g., priming, framing, and decoy effects)
    • Trust inspiring recommendation (e.g., explanation‐aware recommendation)
    • Persuasive recommendation (e.g., argumentation‐aware recommendation)
    • The role of emotions in recommender systems (e.g., emotion‐ware recommendation)
    • Mechanisms for effective group decision making (e.g., group recommendation heuristics)
    • Detection and avoidance of decision biases (e.g., in item presentations)
    • Sequential decision making and selection
    • Applications of the above mentioned features
  • User modeling and preference elicitation
    • Modelling user information search and decision making processes in recommender systems
    • Preference elicitation (e.g., eye tracking for automated preference detection)
    • Adaptive recommendation processes
    • Active approaches to preference elicitation
  • User interfaces
    • User interfaces for decision making (e.g., decision strategies and user ratings)
    • User interfaces for group decision making (e.g., group decision making in e‐tourism)
    • Explanations in Recommender Systems
  • Evaluation
    • User perceptions leading to the acceptance of recommendations
    • The role of diversity and serendipity for the acceptance of recommendations
    • Cultural differences (e.g., culture‐aware recommendation)
    • Empirical studies and innovative metrics of system performance