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In this paper, we present a novel framework for machine learning-based cross-media knowledge extraction. The framework is specifically designed to handle documents composed of three types of media - text, images and raw data - and to exploit the evidence for an extracted fact from across the media. We validate the framework by applying it in the design and development of cross-media extraction systems...
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