Semantic relationship network-based cross-mode information retrieval method

The invention relates to the technical field of information retrieval, in particular a semantic relationship network-based cross-mode information retrieval method. In the method, cross-mode association knowledge is acquired by webpage vision spatial analysis, multimedia search engine label relationship analysis, DeepWe interface mode analysis, analysis on the association of data in different modes in composite multimedia, utilization of direct and potential feedback information of users and association reasoning, and a cross-mode association network is constructed; multimode data sets having the same semanteme and different finenesses are acquired by using the acquired cross-mode association knowledge and hierarchical fuzzy clustering; and typical vectors in different modes are selected from each SC, corresponding semantic vector packets are built, and mapping relations are built among the SCs, the typical vectors and the corresponding semantic vector packets. The method can reduce possible errors in each channel, improve retrieval accuracy effectively, support cross-mode retrievals with semantemes of different finenesses defined by users, and support the retrieval by using multimode data files as samples at the same time.