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SYSTEM AND METHOD FOR PERFORMING CROSS-MODAL INFORMATION RETRIEVAL USING A NEURAL NETWORK USING LEARNED RANK IMAGES
SYSTEM AND METHOD FOR PERFORMING CROSS-MODAL INFORMATION RETRIEVAL USING A NEURAL NETWORK USING LEARNED RANK IMAGES
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机译:使用学习等级图像使用神经网络进行跨模型信息检索的系统和方法
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摘要
A system and method perform cross-modal information retrieval, by generating a graph representing the set of media objects. Each node of the graph corresponds to a media object and is labeled with a set of features corresponding to a text part of the respective media object. Each edge between two nodes represents a similarity between a media part of the two nodes. A first relevance score is computed for each media object of the set of media objects that corresponds to a text-based score. A second relevance score is computed for each media object by inputting the graph into a graph neural network. The first relevance score and the second relevance score are combined to obtain a final ranking score for each media object.
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