Hypothetical Recommendation: A Study of Interactive Profile Manipulation Behavior for Recommender Systems
نویسندگان
چکیده
Explanation and dynamic feedback given to a user during the recommendation process can influence user experience. Despite this, many real-world recommender systems separate profile updates and feedback, obfuscating the relationship between them. This paper studies the effects of what we call hypothetical recommendations. These are recommendations generated by lowcost, exploratory profile manipulations, or “what-if” scenarios. In particular, we evaluate the effects of dynamic feedback from the recommender system on profile manipulations, the resulting recommendations and the user’s overall experience. Results from a user experiment (N=129) suggest that (i) dynamic feedback improves the effectiveness of profile updates, (ii) when dynamic feedback is present, users can identify and remove items that contribute to poor recommendations, (iii) dynamic feedback improves perceived accuracy of recommendations, regardless of actual recommendation
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