Personalized, Interactive Tag Recommendation for Flickr

We study the problem of personalized, interactive tag recommendation for Flickr: While a user enters/selects new tags for a particular picture, the system suggests related tags to her, based on the tags that she or other people have used in the past along with (some of) the tags already entered. The suggested tags are dynamically updated with every additional tag entered/selected. We describe a new algorithm, called Hybrid, which can be applied to this problem, and show that it outperforms previous algorithms. It has only a single tunable parameter, which we found to be very robust.


Publié dans:
Recsys'08: Proceedings Of The 2008 Acm Conference On Recommender Systems, 67-74
Présenté à:
ACM Conference on Recommender Systems, Lausanne, SWITZERLAND, Oct 23-25, 2008
Année
2008
Publisher:
Acm Order Department, P O Box 64145, Baltimore, Md 21264 Usa
ISBN:
978-1-60558-093-7
Mots-clefs:
Laboratoires:




 Notice créée le 2010-11-30, modifiée le 2018-09-13


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