增量聚类算法综述

给出了增量聚类的概念，分析了增量聚类方法可以用于解决数据的变化和大量存储空间的需求问题。增量聚类算法选择恰当时，可以保证数据在变化时有效地提高聚类的精度和效率。从传统聚类、生物智能聚类和数据流聚类三个角度研究了增量聚类问题，分析了增量聚类问题的研究进展，包括发展的过程及特点，阐述了研究增量聚类问题的关键技术，最后给出了未来的发展趋势。

Survey of Incremental Clustering Algorithms

This paper interpreted the concepts of incremental clustering. Because incremental clustering could be used to solve the demands of data changing and large storage space, correct incremental clustering could promoted the accuracy and efficiency of clustering when data was changing. Methods of incremental clustering based on traditional clustering, that based on biological intelligence and stream clustering were studied in this paper and their development process and characteristics were described, and their key technologies were analyzed. Finally, the direction of further work of incremental clustering is given.