Automatic image annotation using visual content and folksonomies
Multimedia Tools and Applications
Quest for relevant tags using local interaction networks and visual content
Proceedings of the international conference on Multimedia information retrieval
Object-based tag propagation for semi-automatic annotation of images
Proceedings of the international conference on Multimedia information retrieval
Modelling image semantic descriptions from web 2.0 documents using a hybrid approach
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
Improving tag recommendation using social networks
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Automatic image semantic interpretation using social action and tagging data
Multimedia Tools and Applications
Tag recommendation for georeferenced photos
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
Image labeling on a network: using social-network metadata for image classification
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Describing locations using tags and images: explorative pattern mining in social media
MSM'11 Proceedings of the 2011 international conference on Modeling and Mining Ubiquitous Social Media
Personalized tag recommendation based on generalized rules
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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Abstract—Imagine you are member of an online social system and want to upload a picture into the community pool. In current social software systems, you can probably tag your photo, share it or send it to a photo printing service and multiple other stuff. The system creates around you a space full of pictures, other interesting content (descriptions, comments) and full of users as well. The one thing current systems do not do, is understand what your pictures are about. We present here a collection of functionalities that make a step in that direction when put together to be consumed by a tag recommendation system for pictures. We use the data richness inherent in social online environments for recommending tags by analysing different aspects of the same data (text, visual contentand user context). We also give an assessment of the quality of thus recommended tags.