Abstract: This work combines semantic reasoning and machine learning to create tools that allow curators of the visual art collections to identify and correct the annotations of the artwork as well as to improve the relevance of the content-based search results in these collections. The research is based on the Joconde database maintained by the French Ministry of Culture that contains illustrated artwork records from main French public and private museums representing archeological objects, decorative arts, fine arts, historical and scientific documents...
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Topics: 
Information retrieval
World Wide Web
Artificial intelligence