Automatic retrieval of network hotspot information based on improved DBSCAN clustering algorithm

With the continuous development of the Internet in the world today, the proliferation of network information makes it difficult for people to effectively screen out current hotspot information. In order to solve the problem of how to retrieve the current hot information quickly and accurately under the massive network information, an automatic network information retrieval method based on the improved DBSCAN clustering algorithm is proposed. The retrieved related keywords are combined to reduce the feature terms, which effectively solves the problem of repeated acquisition of public resource object neighbourhoods, greatly improves the accuracy and efficiency of the clustering algorithm, and realizes automatic retrieval of network information hot spots. The results show that the automatic network information retrieval method based on the improved DBSCAN clustering algorithm proposed in this paper can quickly and accurately find the current information hotspots on the Internet, help users to obtain the hotspot information of their own most interest, and promote the progress and development of the Internet.