The role of transparency in recommender systems Export

@inproceedings{citeulike:201419, abstract = {Recommender Systems act as a personalized decision guides, aiding users in decisions on matters related to personal taste. Most previous research on Recommender Systems has focused on the statistical accuracy of the algorithms driving the systems, with little emphasis on interface issues and the user's perspective. The goal of this research was to examine the role of transprency (user understanding of why a particular recommendation was made) in Recommender Systems. To explore this issue, we conducted a user study of five music Recommender Systems. Preliminary results indicate that users like and feel more confident about recommendations that they perceive as transparent.}, address = {New York, NY, USA}, author = {Sinha, Rashmi and Swearingen, Kirsten}, booktitle = {CHI '02: CHI '02 extended abstracts on Human factors in computing systems}, citeulike-article-id = {201419}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=506619}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/506443.506619}, doi = {10.1145/506443.506619}, isbn = {1-58113-454-1}, keywords = {endorsements}, location = {Minneapolis, Minnesota, USA}, pages = {830--831}, posted-at = {2005-06-03 01:35:36}, priority = {1}, publisher = {ACM}, title = {The role of transparency in recommender systems}, url = {http://dx.doi.org/10.1145/506443.506619}, year = {2002} }

TY - CONF ID - citeulike:201419 L3 - citeulike-article-id:201419 N2 - Recommender Systems act as a personalized decision guides, aiding users in decisions on matters related to personal taste. Most previous research on Recommender Systems has focused on the statistical accuracy of the algorithms driving the systems, with little emphasis on interface issues and the user's perspective. The goal of this research was to examine the role of transprency (user understanding of why a particular recommendation was made) in Recommender Systems. To explore this issue, we conducted a user study of five music Recommender Systems. Preliminary results indicate that users like and feel more confident about recommendations that they perceive as transparent. CY - Minneapolis, Minnesota, USA SN - 1-58113-454-1 AD - New York, NY, USA EP - 831 TI - The role of transparency in recommender systems PB - ACM T2 - CHI '02: CHI '02 extended abstracts on Human factors in computing systems SP - 830 KW - endorsements AU - Sinha, Rashmi AU - Swearingen, Kirsten PY - 2002/// UR - http://dx.doi.org/10.1145/506443.506619 ER -