Research on Improvement Strategy of Clustering Algorithm Based on Density Parameter Optimization Algorithm

In the Internet era, the Internet technology is in a rapid development stage, and more and more fields have introduced clustering algorithms. The main function of this algorithm is to process data information. UIn this case, there is no doubt that clustering algorithm has become a hot research topic for experts and researchers. In many clustering algorithms, the most important application is the clustering algorithm based on the density parameter optimization algorithm. This algorithm is simple and efficient in filtering, so it has received widespread attention from researchers. This paper proposes a clustering algorithm improvement strategy based on the density parameter optimization algorithm. Average clustering algorithm, in order to improve the quality of the algorithm, the nearest neighbor collaborative filtering algorithm can be selected. In addition, this paper optimizes the clustering method and clustering characteristics of the clustering algorithm to be better applied to the data analysis process.