Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Information Retrieval and HyperText
Information Retrieval and HyperText
Towards the Semantic Web: Ontology-driven Knowledge Management
Towards the Semantic Web: Ontology-driven Knowledge Management
A database centric view of semantic image annotation and retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Studying digital imagery of ancient paintings by mixtures of stochastic models
IEEE Transactions on Image Processing
Image retrieval ++--web image retrieval with an enhanced multi-modality ontology
Multimedia Tools and Applications
Incorporating concept ontology into multi-level image indexing
Proceedings of the First International Conference on Internet Multimedia Computing and Service
Going beyond completeness in information retrieval
International Journal of Computational Science and Engineering
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There are hundreds of millions of images available on the current World Wide Web. The demand for image retrieval online is growing dramatically. For multimedia documents, the typical keyword-based retrieval method has encountered problems mainly in the areas of: 1) the quality of the search result; 2) the usage of the system. With the advent and development of the Semantic Web, information retrieval can widely take advantage of this technology which is expected as the next generation of internet. However, before shifting up to the Semantic Web generation, there are still numerous resources on the current Web without semantic annotation. In this paper, we propose a hybrid retrieval method which is based on the current Web, keyword-based annotation structure, and combining Ontology-guided reasoning and probabilistic ranking. A Web application for image retrieval using our proposed approach has been implemented. Furthermore, the system offers recommendations to the user to demonstrate the effectiveness of the model. Experimental results show that the image retrieval recall and precision rates increase by using the proposed hybrid approach.