Research and Evolvement of Data Stream Mining
There are massive, flowing data in telecommunication management, sensor data analyses, financial data account and all other application fields. Toward the high-speed, continuous and abundant data, it demands to access these data timely, effectively and approximately. The traditional data mining methods based on static databases cant deal with this typical data, thus data stream mining technology is appeared. Firstly, this paper introduces the concept and characteristics and analyzes models of data stream, and introduces several comparatively mature data stream management system (DSMS). Then, basing on the international investigation actuality, it dissertate some kinds of representative algorithms in data stream mining. Finally the future study orientation is expected and several noticeable aspects are discussed.
database DSMS classification clustering
Sun Yafeng Yang Xiaopin Huang Zhiping
School of Mechatronic and Automatization, National University of Defense Technology, Changsha, China School of Electrical Engineering, Wuhan University, Wuhan, China, 430072
国际会议
第八届国际测试技术研讨会(8th International Symposium on Test and Measurement)
重庆
英文
1438-1441
2009-08-01（万方平台首次上网日期，不代表论文的发表时间）