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UM
2009
Springer

How Users Perceive and Appraise Personalized Recommendations

12 years 8 months ago
How Users Perceive and Appraise Personalized Recommendations
Abstract. Traditional websites have long relied on users revealing their preferences explicitly through direct manipulation interfaces. However recent recommender systems have gone as far as using implicit feedback indicators to understand users’ interests. More than a decade after the emergence of recommender systems, the question whether users prefer them compared to stating their preferences explicitly, largely remains a subject of study. Even though some studies were found on users’ acceptance and perceptions of this technology, these were general marketing-oriented surveys. In this paper we report an in-depth user study comparing Amazon’s implicit book recommender with a baseline model of explicit search and browse. We address not only the question “do people accept recommender systems” but also how or under what circumstances they do and more importantly, what can still be improved.
Nicolas Jones, Pearl Pu, Li Chen
Added 27 May 2010
Updated 27 May 2010
Type Conference
Year 2009
Where UM
Authors Nicolas Jones, Pearl Pu, Li Chen
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