Tagsplanations: explaining recommendations using tags Export

@inproceedings{citeulike:4036464, abstract = {While recommender systems tell users what items they might like, explanations of recommendations reveal why they might like them. Explanations provide many benefits, from improving user satisfaction to helping users make better decisions. This paper introduces tagsplanations, which are explanations based on community tags. Tagsplanations have two key components: tag relevance, the degree to which a tag describes an item, and tag preference, the user's sentiment toward a tag. We develop novel algorithms for estimating tag relevance and tag preference, and we conduct a user study exploring the roles of tag relevance and tag preference in promoting effective tagsplanations. We also examine which types of tags are most useful for tagsplanations.}, address = {New York, NY, USA}, author = {Vig, Jesse and Sen, Shilad and Riedl, John}, booktitle = {IUI '09: Proceedings of the 13th international conference on Intelligent user interfaces}, citeulike-article-id = {4036464}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1502650.1502661}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1502650.1502661}, doi = {10.1145/1502650.1502661}, isbn = {978-1-60558-168-2}, keywords = {recommender}, location = {Sanibel Island, Florida, USA}, pages = {47--56}, posted-at = {2009-08-13 09:54:14}, priority = {4}, publisher = {ACM}, title = {Tagsplanations: explaining recommendations using tags}, url = {http://dx.doi.org/10.1145/1502650.1502661}, year = {2009} }

TY - CONF ID - citeulike:4036464 L3 - citeulike-article-id:4036464 N2 - While recommender systems tell users what items they might like, explanations of recommendations reveal why they might like them. Explanations provide many benefits, from improving user satisfaction to helping users make better decisions. This paper introduces tagsplanations, which are explanations based on community tags. Tagsplanations have two key components: tag relevance, the degree to which a tag describes an item, and tag preference, the user's sentiment toward a tag. We develop novel algorithms for estimating tag relevance and tag preference, and we conduct a user study exploring the roles of tag relevance and tag preference in promoting effective tagsplanations. We also examine which types of tags are most useful for tagsplanations. CY - Sanibel Island, Florida, USA SN - 978-1-60558-168-2 AD - New York, NY, USA EP - 56 TI - Tagsplanations: explaining recommendations using tags PB - ACM T2 - IUI '09: Proceedings of the 13th international conference on Intelligent user interfaces SP - 47 KW - recommender AU - Vig, Jesse AU - Sen, Shilad AU - Riedl, John PY - 2009/// UR - http://dx.doi.org/10.1145/1502650.1502661 ER -