The invention discloses a hierarchical tag-based cross-
modal Hash model construction method, a search method and a device. The method comprises the following steps of receiving a multi-
modal data set,and preprocessing; inputting the relative data of the preprocessed data of different modalities into a pre-trained multi-path neural network; according to the pre-trained neural network and the multi-layer
perceptron, extracting the characteristic data of different
modes respectively, and obtaining the hierarchical Hash representations of different
modes; constructing the similarity matrixes of the preprocessed samples on different levels according to the level labels, and evaluating the
semantic similarity among the samples according to the inner product of the Hash representation trained bythe median of each level of
similarity matrix; adopting the hierarchical labels with different granularities, analyzing the influence of the hierarchical comparison on the neural
network performance,and determining the optimal hierarchical ratio; obtaining a Hash code according to each layer of Hash representation; and training the dual-path neural network, optimizing and training the dual-pathneural network by using an SGD
gradient descent method, and establishing a deep cross-
modal hash model based on hierarchical tags for cross-modal search.