Construction of Korean Teaching Resource Library Based on Python Crawler

The information in the Internet is increasing geometrically, and it is very difficult for users to collect the desired Korean teaching resources information in the network. This paper proposes a data collection method based on Python crawler. The theme of this study is to study the application of deep learning web crawler algorithm based on big data in the information collection and processing of Korean teaching resources. In this paper, the neural network resources are modified, and the propagation activation algorithm is combined to realize the grabbing of web page resources. Combined with the results of experimental analysis, it can be seen that the coverage rate of the algorithm proposed in this paper is much higher than that of traditional algorithms, and the data acquisition and processing speed of the algorithm proposed in this paper is higher than that of existing algorithm models, which means that the algorithm can collect and process data more comprehensively and help to better improve the quality and integrity of information in the process of obtaining information.