针对高属性维稀疏数据聚类问题，提出高属性维稀疏信息系统概念，给出一种新的基于稀疏特征差异度的动态抽象聚类方法。
The concepts of high attribute dimensional information system are firstly proposed, and a new dynamic clustering method on the basis of sparse feature difference degree is presented.
在叙述实际应用的基础上抽象出最优位置查询概念，提出目标对象的优先权度量标准、删减数据对象的启发式规则和最优位置查询算法，分析最优位置查询算法的时间复杂度。
After describing real application, it presents the best location query, the priority of target object, the heuristic rule to delete data objects, and analyzes the time complexity of the algorithm.
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