Application of Density Clustering Algorithm Based on Greedy Strategy in Hot Spot Mining of Taxi Passengers

In this paper, the greedy strategy is used to improve the density clustering algorithm, which can separate the noise points and deal with the uneven density distribution. In order to further improve the efficiency of density clustering algorithm based on greedy strategy, in this paper, it is applied to mining hot spots of taxi passengers. Firstly, large-scale data are processed, and large-scale data sets are sampled by reservoir, and effective hot data are obtained. Then, the data of 8,000 taxis in an urban area during December 4–8, 2018 are clustered to verify the validity of the proposed algorithm.