Research on a scalable parallel data mining algorithm
Wang ; Jinlin1 ; 2 ; Chen ; Xi1 ; Zhou ; Kefa1
2009
会议名称5th International Joint Conference on INC, IMS, and IDC
会议日期2009
会议地点Seoul, Korea, Republic of
关键词Computational complexity - Computational efficiency - Information management - Parallel algorithms - Research - Semiconductor storage - Active field - Data mining algorithm - Domain of knowledge - Experimental verification - Hardware and software - Massive data - Network monitoring systems - Parallel data mining - Projection database - Real-world application - Sensor grids - Sequential patterns - Sequential-pattern mining - Spatial complexity - Streaming data
页码888-893
中文摘要Sequential pattern mining is an active field in the domain of knowledge discovery and has been widely studied for over a decade by data mining researchers. More and more, with the constant progress in hardware and software technologies, real-world applications like network monitoring systems or sensor grids generate huge amount of streaming data. These works need an efficient and scalable parallel algorithm. On the basis of the widespread problem in current sequential pattern data mining algorithm and researching the data mining algorithm of serial sequential pattern, this paper proposes sequential patterns based and projection database based algorithm for scalable parallel sequential patterns data mining algorithm. Through theoretical analysis and experimental verification, the parallel data mining algorithm can well reduce the computational and spatial complexity and improve the efficiency of data mining in massive data circumstances. © 2009 IEEE. (16 refs.)
收录类别EI
会议录NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC
ISBN号13: 9780769537696
内容类型会议论文
源URL[http://ir.xjlas.org/handle/365004/10852]  
专题新疆生态与地理研究所_中国科学院新疆生态与地理研究所(2010年以前数据)
推荐引用方式
GB/T 7714
Wang,Jinlin1,2,et al. Research on a scalable parallel data mining algorithm[C]. 见:5th International Joint Conference on INC, IMS, and IDC. Seoul, Korea, Republic of. 2009.
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