Tagsplanations: explaining recommendations using tags
J. Vig, S. Sen, и J. Riedl. IUI '09: Proceedingsc of the 13th international conference on Intelligent user interfaces, стр. 47--56. New York, NY, USA, ACM, (2008)
DOI: 10.1145/1502650.1502661
Аннотация
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.
%0 Conference Paper
%1 citeulike:4036464
%A Vig, Jesse
%A Sen, Shilad
%A Riedl, John
%B IUI '09: Proceedingsc of the 13th international conference on Intelligent user interfaces
%C New York, NY, USA
%D 2008
%I ACM
%K explanation recommender tagging
%P 47--56
%R 10.1145/1502650.1502661
%T Tagsplanations: explaining recommendations using tags
%U http://dx.doi.org/10.1145/1502650.1502661
%X 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.
%@ 978-1-60558-168-2
@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.},
added-at = {2009-07-01T11:12:30.000+0200},
address = {New York, NY, USA},
author = {Vig, Jesse and Sen, Shilad and Riedl, John},
biburl = {https://www.bibsonomy.org/bibtex/21e74fa227a24f49d8f6b17a02ea96db5/brusilovsky},
booktitle = {IUI '09: Proceedingsc of the 13th international conference on Intelligent user interfaces},
citeulike-article-id = {4036464},
doi = {10.1145/1502650.1502661},
interhash = {a6d866cf13c75130c1969c9e40606fd1},
intrahash = {1e74fa227a24f49d8f6b17a02ea96db5},
isbn = {978-1-60558-168-2},
keywords = {explanation recommender tagging},
location = {Sanibel Island, Florida, USA},
pages = {47--56},
posted-at = {2009-02-11 19:44:31},
priority = {4},
publisher = {ACM},
timestamp = {2009-07-01T11:12:33.000+0200},
title = {Tagsplanations: explaining recommendations using tags},
url = {http://dx.doi.org/10.1145/1502650.1502661},
year = 2008
}