Christine Bauer, Markus Schedl,
"Introducing Surprise and Opposition by Design in Recommender Systems."
: 25th International Conference on User Modeling, Adaptation and Personalization (UMAP 2017): 2nd Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP 2017), Seite(n) 350 - 353, 7-2017
Original Titel:
Introducing Surprise and Opposition by Design in Recommender Systems.
Sprache des Titels:
Englisch
Original Buchtitel:
25th International Conference on User Modeling, Adaptation and Personalization (UMAP 2017): 2nd Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP 2017)
Original Kurzfassung:
Œere is a long tradition in recommender systems research to evaluate
systems using quantitative performance measures on €xed
datasets. As a reaction to this narrow accuracy-based focus in research,
novel qualities beyond pure accuracy are emphasized in
recent research; among them are surprise and opposition.
Œis position paper considers that the perception of surprise
and/or opposition may be purposely prepared when several recommendations
are provided (e.g., in terms of a music playlist) or the
user is given the choice between several options.
Altering users? perception and triggering according behavior
is well rooted in research on priming from psychology and nudge
theory from the €eld of economic behavior.
In this position paper, we propose how priming and nudging
may be integrated into the design and evaluation of recommender
systems to arouse surprise and opposition.
Forschungs-