Under the background of the development of the network information age, the current Internet industry has obtained more development opportunities, but it has also brought corresponding challenges in the process of wide application. In the development and construction of modernization, society pays more attention to the supervision and determination of the characteristics of online public opinion. From the perspective of the current characteristics of network public opinion, because social information is more extensive and involves many fields, network public opinion has a high degree of complexity and diffusion. Therefore, it is necessary to strengthen the analysis and application of relevant data mining systems in order to achieve efficient management of network public opinion. The key to the disadvantage of the traditional excavation of public opinion communication characteristics lies in the lag of the excavation process, and it is difficult to deal with malignant public opinion in a timely and effective manner. Therefore, in order to truly solve the lagging problem of public opinion data dissemination feature mining technology, it is necessary to strengthen the application of artificial intelligence technology in it.

At this stage, network technology is developing rapidly. The resources in the network are massive, and a large number of resources are distributed in a decentralized and heterogeneous manner. With the continuous expansion of the application scope of distributed technology, it can provide effective scheme guidance for resource application. Combined with the current situation of network teaching platform and relevant functional requirements, it is very necessary to apply distributed technology. Taking DFS technology as an example, this paper studies the shared resource management scheme of this technology in network storage, and studies the specific application effect and path of DFS technology in distributed network teaching platform.