关键词: 聚类, 数据流, 网格, 参数自适应, 密度阈值

Abstract: For the problem that traditional density grid-based stream clustering algorithm cannot get accurate density value, this paper introduces a new density grid-based stream clustering algorithm with parameter automatization A-Stream. Through the introduction of the double density, the traditional density grid-based clustering algorithm for data stream is improved by taking the average as the grid density, resolving the problem that algorithm cannot get accurate value automatically. The experimental results show that not only the high efficiency of the grid-based algo-rithm is utilized, but also the clustering accuracy is raised significantly.

Key words: clustering, data stream, grid, parameter adaptation, density threshold