Faceted search and retrieval based on semantically annotated product family ontology
Proceedings of the WSDM '09 Workshop on Exploiting Semantic Annotations in Information Retrieval
Information Processing and Management: an International Journal
Knowledge retrieval in the anatomical domain
Proceedings of the 1st ACM International Health Informatics Symposium
Image annotation based on central region features reduction
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Mining image databases by content
BNCOD'11 Proceedings of the 28th British national conference on Advances in databases
Interactive navigation of image collections
FGIT'11 Proceedings of the Third international conference on Future Generation Information Technology
Interactive Exploration of Large Photo Libraries
Proceedings of the Second International Conference on Innovative Computing and Cloud Computing
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Most public image retrieval engines utilise free-text search mechanisms, which often return inaccurate matches as they in principle rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this paper we present a semantically-enabled image annotation and retrieval engine that relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. Our semantic retrieval technology is designed to satisfy the requirements of the commercial image collections market in terms of both accuracy and efficiency of the retrieval process. We also present our efforts in further improving the recall of our retrieval technology by deploying an efficient query expansion technique.