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ENHANCED MAX MARGIN LEARNING ON MULTIMODAL DATA MINING IN A MULTIMEDIA DATABASE
ENHANCED MAX MARGIN LEARNING ON MULTIMODAL DATA MINING IN A MULTIMEDIA DATABASE
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机译:增强多媒体数据库中多模态数据挖掘的最大利润率学习
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摘要
Multimodal data mining in a multimedia database is addressed as a structured prediction problem, wherein mapping from input to the structured and interdependent output variables is learned. A system and method for multimodal data mining is provided, comprising defining a multimodal data set comprising image information; representing image information of a data object as a set of feature vectors in a feature space; clustering in the feature space to group similar features; associating a non-image representation with a respective image data object based on the clustering; determining a joint feature representation of a respective data object as a mathematical weighted combination of a set of components of the joint feature representation; optimizing a weighting for a plurality of components of the mathematical weighted combination with respect to a prediction error between a predicted classification and a training classification; and employing the mathematical weighted combination for automatically classifying a new data object.
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