Design of WeChat teaching information retrieval platform based on DCMH

Deep Semantic Multimodal Hashing (DCMH) is a cross-modal hash retrieval method based on a deep learning framework that combines deep feature learning and hash learning. The method uses the extracted text and image data features as hash codes to form an end-to-end network of directly discrete optimized binary hash codes. In the era of new media, the WeChat public platform is one of the most important channels for teaching information services in colleges and universities, so that information services can directly point to the needs of teachers and students. Using the WeChat public account as the front end , based on DCMH, a method of extracting fine-grained features on images and texts was designed, and it set up feature learning and label prediction for multi-modal data, built a multi-modal retrieval platform based on WeChat public account, and designed DCMH-based feature training data mining and public account front multimodal data interaction model diagram, keeping up with the digital age to meet the development requirements, to achieve a major change in teaching management, and improve the efficiency and level of service.