TY - GEN
T1 - How users perceive and appraise personalized recommendations
AU - Jones, Nicolas
AU - Pu, Pearl
AU - Chen, Li
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=70349816401&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-02247-0_53
DO - 10.1007/978-3-642-02247-0_53
M3 - Conference proceeding
AN - SCOPUS:70349816401
SN - 3642022464
SN - 9783642022463
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 461
EP - 466
BT - User Modeling, Adaptation, and Personalization - 17th International Conference, UMAP 2009 formerly UM and AH, Proceedings
T2 - 17th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2009
Y2 - 22 June 2009 through 26 June 2009
ER -