Making recommendations for social media presents
special challenges. As tagging becomes common practice
at many social media sites, this research proposes
a new approach to user profiling based on the tags associated
with one’s personal collection of contents. To
utilize the social interaction implied by tagging, a personal
profile can be further extended with the tags specified
by one’s social contacts. A tag-to-tag matrix is defined
to enable collaborative filtering-style recommendations
without explicit user ratings. Experiments with
collections of bookmarks and the associated tags from
42,463 users are presented and compared using the different
views.
%0 Journal Article
%1 huang2008
%A Hung, C.C.
%A Huang, Y.C.
%A Hsu, J.Y.
%A Wu, D.K.C.
%B Workshop on Intelligent Techniques for Web Personalization & Recommender Systems at AAAI2008, Chicago, Illinois
%D 2008
%K recsys tag tag_profile
%T Tag-Based User Profiling for Social Media Recommendation
%X Making recommendations for social media presents
special challenges. As tagging becomes common practice
at many social media sites, this research proposes
a new approach to user profiling based on the tags associated
with one’s personal collection of contents. To
utilize the social interaction implied by tagging, a personal
profile can be further extended with the tags specified
by one’s social contacts. A tag-to-tag matrix is defined
to enable collaborative filtering-style recommendations
without explicit user ratings. Experiments with
collections of bookmarks and the associated tags from
42,463 users are presented and compared using the different
views.
@article{huang2008,
abstract = {Making recommendations for social media presents
special challenges. As tagging becomes common practice
at many social media sites, this research proposes
a new approach to user profiling based on the tags associated
with one’s personal collection of contents. To
utilize the social interaction implied by tagging, a personal
profile can be further extended with the tags specified
by one’s social contacts. A tag-to-tag matrix is defined
to enable collaborative filtering-style recommendations
without explicit user ratings. Experiments with
collections of bookmarks and the associated tags from
42,463 users are presented and compared using the different
views.},
added-at = {2014-03-01T14:41:14.000+0100},
author = {Hung, C.C. and Huang, Y.C. and Hsu, J.Y. and Wu, D.K.C.},
biburl = {https://www.bibsonomy.org/bibtex/26e8f142eb28390f67bbab009ea7e4818/inmantang},
booktitle = {Workshop on Intelligent Techniques for Web Personalization \& Recommender Systems at AAAI2008, Chicago, Illinois},
ee = {https://www.aaai.org/Papers/Workshops/2008/WS-08-06/WS08-06-006.pdf},
interhash = {699213a48bbee1c9287589021e9c588f},
intrahash = {6e8f142eb28390f67bbab009ea7e4818},
keywords = {recsys tag tag_profile},
timestamp = {2014-03-01T14:41:14.000+0100},
title = {{Tag-Based User Profiling for Social Media Recommendation}},
year = 2008
}