Flickr Tag Recommendation based on Collective Knowledge
Börkur Sigurbjörnsson, and Roelof van Zwol.
In: Proceedings of the 17th International World Wide Web Conference (WWW’08).
Link: acm
Abstract
Online photo services such as Flickr and Zooomr allow users to share their photos with family, friends, and the online community at large. An important facet of these services is that users manually annotate their photos using so called tags, which describe the contents of the photo or provide additional contextual and semantical information. In this paper we investigate how we can assist users in the tagging phase. The contribution of our research is twofold. We analyse a representative snapshot of Flickr and present the results by means of a tag characterisation focussing on how users tags photos and what information is contained in the tagging. Based on this analysis, we present and evaluate tag recommendation strategies to support the user in the photo annotation task by recommending a set of tags that can be added to the photo. The results of the empirical evaluation show that we can effectively recommend relevant tags for a variety of photos with different levels of exhaustiveness of original tagging.
Bibtex
@inproceedings{sigurbjornsson2008flickr, author = {B"{o}rkur Sigurbj"{o}rnsson and Roelof van Zwol}, title = {Flickr tag recommendation based on collective knowledge}, booktitle = {WWW '08: Proceeding of the 17th international conference on World Wide Web}, year = {2008}, isbn = {978-1-60558-085-2}, pages = {327--336}, location = {Beijing, China}, doi = {http://doi.acm.org/10.1145/1367497.1367542}, publisher = {ACM}, address = {New York, NY, USA}, }