Research on Cross-media Semantic Retrieval Methods of Information Resources Based on Deep Learning

This paper is to study cross-media semantic retrieval method of information resources based on deep learning. By analyzing the concept of deep learning, the depth structure and the prerequisites for deep learning, this paper studies the relationship between deep learning and information resources cross-media semantic retrieval, and points out the cross-media correlation learning technology of information resources on the basis of depth structure, buildings a distinct framework for information retrieval. As a new information retrieval model, the combination of deep learning and cross-media semantic retrieval can solve the problems of retrieving semantic information across the media and processing complex dimensional data, greatly improving the efficiency of data retrieval and integration. This model will replace the existing information retrieval tools, to become a sword to enhance the level of knowledge service in the era of big data.