Personalized Tag Recommendations via Tagging and Content-based Similarity Metrics
A. Byde, H. Wan, und S. Cayzer.
Proceedings of the International Conference on Weblogs and Social Media, (März 2007)

This short paper describes a novel technique for generating personalized tag recommendations for users of social book- marking sites such as del.icio.us. Existing techniques recom- mend tags on the basis of their popularity among the group of all users; on the basis of recent use; or on the basis of simple heuristics to extract keywords from the url being tagged. Our method is designed to complement these approaches, and is based on recommending tags from urls that are similar to the one in question, according to two distinct similarity metrics, whose principal utility covers complementary cases.

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@inproceedings{byde2007personalized,
  abstract = {This short paper describes a novel technique for generating personalized
	tag recommendations for users of social book- marking sites such
	as del.icio.us. Existing techniques recom- mend tags on the basis
	of their popularity among the group of all users; on the basis of
	recent use; or on the basis of simple heuristics to extract keywords
	from the url being tagged. Our method is designed to complement these
	approaches, and is based on recommending tags from urls that are
	similar to the one in question, according to two distinct similarity
	metrics, whose principal utility covers complementary cases.},
  added-at = {2008-10-16T17:21:28.000+0200},
  author = {Byde, Andrew and Wan, Hui and Cayzer, Steve},
  biburl = {https://puma.uni-kassel.de/bibtex/2157846898c1c2a65c265a913ebac115a/jaeschke},
  booktitle = {Proceedings of the International Conference on Weblogs and Social
	Media},
  interhash = {38aaca7e5b9c508a5901f4109dabaa69},
  intrahash = {157846898c1c2a65c265a913ebac115a},
  keywords = {content recommender similarity tag tagging},
  month = {March},
  timestamp = {2008-10-16T17:21:28.000+0200},
  title = {Personalized Tag Recommendations via Tagging and Content-based Similarity Metrics},
  url = {http://www.icwsm.org/papers/paper47.html},
  year = 2007
}

%0 Conference Paper
%1 byde2007personalized
%A Byde, Andrew
%A Wan, Hui
%A Cayzer, Steve
%B Proceedings of the International Conference on Weblogs and Social
	Media
%D 2007
%K content recommender similarity tag tagging
%T Personalized Tag Recommendations via Tagging and Content-based Similarity Metrics
%U http://www.icwsm.org/papers/paper47.html
%X This short paper describes a novel technique for generating personalized
	tag recommendations for users of social book- marking sites such
	as del.icio.us. Existing techniques recom- mend tags on the basis
	of their popularity among the group of all users; on the basis of
	recent use; or on the basis of simple heuristics to extract keywords
	from the url being tagged. Our method is designed to complement these
	approaches, and is based on recommending tags from urls that are
	similar to the one in question, according to two distinct similarity
	metrics, whose principal utility covers complementary cases.

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Personalized Tag Recommendations via Tagging and Content-based Similarity Metrics
A. Byde, H. Wan, und S. Cayzer.
Proceedings of the International Conference on Weblogs and Social Media, (März 2007)

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PUMA

Personalized Tag Recommendations via Tagging and Content-based Similarity MetricsA. Byde, H. Wan, und S. Cayzer. Proceedings of the International Conference on Weblogs and Social Media, (März 2007)

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Personalized Tag Recommendations via Tagging and Content-based Similarity Metrics
A. Byde, H. Wan, und S. Cayzer.
Proceedings of the International Conference on Weblogs and Social Media, (März 2007)