Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Advanced Interaction in Context
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
A Survey of Context-Aware Mobile Computing Research
A Survey of Context-Aware Mobile Computing Research
Leveraging context to resolve identity in photo albums
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Proceedings of the 15th international conference on World Wide Web
CONFOTO: Browsing and annotating conference photos on the Semantic web
Web Semantics: Science, Services and Agents on the World Wide Web
Classification and annotation of digital photos using optical context data
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Spirittagger: a geo-aware tag suggestion tool mined from flickr
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Analysis of a Real Online Social Network Using Semantic Web Frameworks
ISWC '09 Proceedings of the 8th International Semantic Web Conference
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
Improving face recognition with genealogical and contextual data
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
| Hi-index | 0.00 |
We purpose a system that can semi-automatically generate ontology-based annotations for a social network by leveraging the annotations provided by the most active user (also known as the central actor). Social context of an image is of central importance in our approach towards semantic semi-automatic annotation. For the context of an image, we consider several factors like geo-reference, time and relationship among actors in social networks. Our system leverages the context, which is automatically available along with the image. We have also extended Social Network Analysis techniques by considering the granularity of relationships among actors under consideration. In this paper a semantic web framework is used to represent the social network and to deal with the diversity of relationships. OntoCAIM ontology is developed which not only encompasses Social Network Analysis functionality but also defines mechanism to annotate images with an underlying ontology.