.... Design/methodology/approach We comprehensively measured 28 multimodal characteristics across four dimensions: style, quantity, quality, and complexity using deep learning techniques. An empirical analysis was then conducted on 4,665 health-related WeChat posts spanning multiple types of health topics...

..., images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data. Design...

... framework, including four pivotal stages: knowledge element description, extraction, association and application. Initially, a semantic description model dedicated to knowledge elements is devised. Subsequently, harnessing the advanced deep learning techniques, the study delves into the realm of entity...

... in appropriately managing their diseases. Therefore, this paper aims to introduce a novel deep learning-based method that allows non-professionals to make inquiries using ordinary vocabulary, retrieving the most relevant case reports for accurate and effective health information. Design/methodology/approach...

... in the knowledge graph and improving the application effect of the knowledge graph in information retrieval, question answering and other fields. Recently, deep learning methods such as CNNs, graph convolutional networks (GCNs), and graph attention networks (GATs) have been widely applied to knowledge graph...

... books, to solve the problem. Findings The application of deep learning in book purchase task is effective. The data the authors exploited are the historical book purchase data from their university library. The authors’ experiments on the data show that ALBERT-BPF can seek out the books that need...