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definition of the high-level concepts the user queries for (semantic objects, each represented by a keyword) and their relations in a human-centered fashion. When querying for a specific semantic object (or objects), the intermediate-level descriptor values associated with both the semantic object and all image
associated with intermediate semantic descriptors. The intermediate descriptors are used also for image categorization and for qualitative definition of semantic keywords in the user queries. For improving the initial query results, we apply a relevance feedback mechanism that uses the low -level descriptors of the images
Image annotation is usually formed as a multiclass classification problem. Traditional methods learn the co-occurrence of keywords and images while they ignore the correlation between keywords, which turned out to be one of the reasons causing poor experiment results. In this paper, we propose an automatic image
index texts. Traditional BOW matrix is replaced by ldquoBag of Conceptsrdquo (BOC). For this purpose, we developed fully automated methods for mapping keywords to their corresponding ontology concepts. Support vector machine a successful machine learning technique is used for classification. Experimental results shows that
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