RESOURCE-AWARE HIGH QUALITY CLUSTERING IN UBIQUITOUS DATA STREAMS

摘要：

Data stream mining has attracted much research attention from the data mining community. With the advance of wireless networks and mobile devices, the concept of ubiquitous data mining has been proposed. However, mobile devices are resource-constrained, which makes data stream mining a greater challenge. In this paper, we propose the RA-HCluster algorithm that can be used in mobile devices for clustering stream data. It adapts algorithm settings and compresses stream data based on currently available resources, so that mobile devices can continue with clustering at acceptable accuracy even under low memory resources. Experimental results show that not only is RA-HCluster more accurate than RA-VFKM, it is able to maintain a low and stable memory usage.

关键词： Data Mining Data Streams Clustering Ubiquitous Data Mining Ubiquitous Data Stream Mining

作者: Ching-Ming Chao Guan-Lin Chao

作者单位: Department of Computer Science and Information Management, Soochow University, Chinese Taiwan Department of Electrical Engineering, National Taiwan University, Chinese Taiwan

会议类型: 国际会议

会议名称: 13th International Conference on Enterprise Information System(第13届企业信息系统国际会议 ICEIS 2011)

会议地点: 北京

会议语种:英文

页码: 1964-1973

在线出版日期: 2011-06-08（万方平台首次上网日期，不代表论文的发表时间）