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ABSTRACT
We describe an approach for extracting semantics of tags, unstructured text-labels assigned to resources on the Web, based on each tag's usage patterns. In particular, we focus on the problem of extracting place and event semantics for tags that are assigned to photos on Flickr, a popular photo sharing website that supports time and location (latitude/longitude) metadata. We analyze two methods inspired by well-known burst-analysis techniques and one novel method: Scale-structure Identification. We evaluate the methods on a subset of Flickr data, and show that our Scale-structure Identification method outperforms the existing techniques. The approach and methods described in this work can be used in other domains such as geo-annotated web pages, where text terms can be extracted and associated with usage patterns.
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CITED BY 21
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Lyndon Kennedy , Mor Naaman , Shane Ahern , Rahul Nair , Tye Rattenbury, How flickr helps us make sense of the world: context and content in community-contributed media collections, Proceedings of the 15th international conference on Multimedia, September 25-29, 2007, Augsburg, Germany
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Kerstin Bischoff , Claudiu S. Firan , Wolfgang Nejdl , Raluca Paiu, How do you feel about "dancing queen"?: deriving mood & theme annotations from user tags, Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries, June 15-19, 2009, Austin, TX, USA
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Fabian Abel , Matteo Baldoni , Cristina Baroglio , Nicola Henze , Daniel Krause , Viviana Patti, Context-based ranking in folksonomies, Proceedings of the 20th ACM conference on Hypertext and hypermedia, June 29-July 01, 2009, Torino, Italy
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