%0 Conference Paper %1 plangprasopchok2009 %A Plangprasopchok, A. %A Lerman, K. %B WWW '09: Proceedings of the 18th international conference on World wide web %C New York, NY, USA %D 2009 %I ACM %K folksonomy learning ol relation tagging taggingsurvey %P 781--790 %R http://doi.acm.org/10.1145/1526709.1526814 %T Constructing folksonomies from user-specified relations on flickr %U http://www2009.org/proceedings/pdf/p781.pdf %X Automatic folksonomy construction from tags has attracted much attention recently. However, inferring hierarchical relations between concepts from tags has a drawback in that it is difficult to distinguish between more popular and more general concepts. Instead of tags we propose to use user-specified relations for learning folksonomy. We explore two statistical frameworks for aggregating many shallow individual hierarchies, expressed through the collection/set relations on the social photosharing site Flickr, into a common deeper folksonomy that reflects how a community organizes knowledge. Our approach addresses a number of challenges that arise while aggregating information from diverse users, namely noisy vocabulary, and variations in the granularity level of the concepts expressed. Our second contribution is a method for automatically evaluating learned folksonomy by comparing it to a reference taxonomy, e.g., the Web directory created by the Open Directory Project. Our empirical results suggest that user-specified relations are a good source of evidence for learning folksonomies. %@ 978-1-60558-487-4

@inproceedings{plangprasopchok2009, abstract = {Automatic folksonomy construction from tags has attracted much attention recently. However, inferring hierarchical relations between concepts from tags has a drawback in that it is difficult to distinguish between more popular and more general concepts. Instead of tags we propose to use user-specified relations for learning folksonomy. We explore two statistical frameworks for aggregating many shallow individual hierarchies, expressed through the collection/set relations on the social photosharing site Flickr, into a common deeper folksonomy that reflects how a community organizes knowledge. Our approach addresses a number of challenges that arise while aggregating information from diverse users, namely noisy vocabulary, and variations in the granularity level of the concepts expressed. Our second contribution is a method for automatically evaluating learned folksonomy by comparing it to a reference taxonomy, e.g., the Web directory created by the Open Directory Project. Our empirical results suggest that user-specified relations are a good source of evidence for learning folksonomies.}, added-at = {2010-03-20T21:36:19.000+0100}, address = {New York, NY, USA}, author = {Plangprasopchok, A. and Lerman, K.}, biburl = {https://www.bibsonomy.org/bibtex/2559ee9d48f1a510f56765b2357aa8ea5/hotho}, booktitle = {WWW '09: Proceedings of the 18th international conference on World wide web}, doi = {http://doi.acm.org/10.1145/1526709.1526814}, interhash = {fccd894a82edb040d7438d6da91e3ebe}, intrahash = {559ee9d48f1a510f56765b2357aa8ea5}, isbn = {978-1-60558-487-4}, keywords = {folksonomy learning ol relation tagging taggingsurvey}, location = {Madrid, Spain}, pages = {781--790}, publisher = {ACM}, timestamp = {2012-01-25T16:44:24.000+0100}, title = {Constructing folksonomies from user-specified relations on flickr}, url = {http://www2009.org/proceedings/pdf/p781.pdf}, year = 2009 }