Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Proceedings of the seventeenth conference on Hypertext and hypermedia
Towards automatic extraction of event and place semantics from flickr tags
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Inferring generic activities and events from image content and bags of geo-tags
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Classifying tags using open content resources
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Proceedings of the 18th international conference on World wide web
Event detection from flickr data through wavelet-based spatial analysis
Proceedings of the 18th ACM conference on Information and knowledge management
Not all tags are created equal: learning Flickr tag semantics for global annotation
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Event Clusters Detection on Flickr Images Using a Suffix-Tree Structure
ISM '10 Proceedings of the 2010 IEEE International Symposium on Multimedia
A two-view learning approach for image tag ranking
Proceedings of the fourth ACM international conference on Web search and data mining
Generating links to background knowledge: a case study using narrative radiology reports
Proceedings of the 20th ACM international conference on Information and knowledge management
Statistical Methods for Disease Clustering
Statistical Methods for Disease Clustering
RESLVE: leveraging user interest to improve entity disambiguation on short text
Proceedings of the 22nd international conference on World Wide Web companion
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Media sharing applications such as Panoramio and Flickr contain a huge amount of pictures that need to be organized to facilitate browsing and retrieval. Such pictures are often surrounded by a set of metadata or image tags, constituting the image context. With the advent of the paradigm of Web 2.0 especially the past five years, the concept of image context has further evolved, allowing users to tag their own and other people's pictures. Focusing on tagging, we distinguish between static and dynamic features. The set of static features include textual and visual features, as well as the contextual information. Further, we may identify other features belonging to the social context as a result of the usage within the media sharing applications. Due to their dynamic nature, we call these the dynamic set of features. In this work, we assume that every media uploaded contains both static and dynamic features. In addition, a user may be linked with other users with whom he/she shares common interests. This has resulted in a new series of challenges within the research field of semantic understanding. One of the main goals of this work is to address these challenges.