Using semantic contents and WordNet in image retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
International Journal of Computer Vision
Ontology-enriched semantic space for video search
Proceedings of the 15th international conference on Multimedia
Autonomously semantifying wikipedia
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Wikify!: linking documents to encyclopedic knowledge
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A knowledge-based search engine powered by wikipedia
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
OntoSearch: a full-text search engine for the semantic web
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Coloring local feature extraction
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Learning and inferencing in user ontology for personalized Semantic Web search
Information Sciences: an International Journal
Wikipedia-assisted concept thesaurus for better web media understanding
Proceedings of the international conference on Multimedia information retrieval
Multipedia: enriching DBpedia with multimedia information
Proceedings of the sixth international conference on Knowledge capture
Proceedings of the 21st ACM international conference on Information and knowledge management
Image retrieval using eigen queries
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
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Ontology, as an effective approach to bridge the semantic gap in various domains, has attracted a lot of interests from multimedia researchers. Among the numerous possibilities enabled by ontology, we are particularly interested in exploiting ontology for a better understanding of media task (particularly, images) on the World Wide Web. To achieve our goal, two open issues are inevitably involved: 1) How to avoid the tedious manual work for ontology construction? 2) What are the effective inference models when using an ontology? Recent works[11, 16] about ontology learned from Wikipedia has been reported in conferences targeting the areas of knowledge management and artificial intelligent. There are also reports of different inference models being investigated [5, 13, 15]. However, so far there has not been any comprehensive solution. In this paper, we look at these challenges and attempt to provide a general solution to both questions. Through a careful analysis of the online encyclopedia Wikipedia's categorization and page content, we choose it as our knowledge source and propose an automatic ontology construction approach. We prove that it is a viable way to build ontology under various domains. To address the inference model issue, we provide a novel understanding of the ontology and consider it as a type of semantic network, which is similar to brain models in the cognitive research field. Spreading Activation Techniques, which have been proved to be a correct information processing model in the semantic network, are consequently introduced for inference. We have implemented a prototype system with the developed solutions for web image retrieval. By comprehensive experiments on the canine category of the animal kingdom, we show that this is a scalable architecture for our proposed methods.