Research onCross-media Semantic Retrieval in Digital Library Based on Deep Learning

A diverse and heterogeneous data environment, an excellent cross-media semantic retrieval model is the key to enhancing the interactivity of digital libraries and promoting the upgrading of their knowledge services. On the basis of analyzing the theoretical concept of deep learning, characteristics of deep structure, related technologies, and correlation between cross-media semantic retrieval and deep learning, this study constructs a cross-media semantic retrieval framework based on deep learning. Research suggests that the combination of deep learning and cross-media semantic retrieval, as a new information retrieval model in digital libraries, helps to solve the problems of searching for semantic information across media and efficiently processing complex dimensional data, greatly improving the efficiency of data retrieval and integration. It will inevitably accelerate improving knowledge service levels in the era of big data. The study provides reference for improving the effectiveness of cross-media semantic retrieval for library users and improving library knowledge organization and services.