GMDBSCAN: Multi-Density DBSCAN Cluster Based on Grid

摘要：

DBSCAN is one of the most popular algorithms for cluster analysis. It can discover all clusters with arbitrary shape and separate noises. But this algorithm cant choose parameter according to distributing of dataset. It simply uses the global MinPts parameter, so that the clustering result of multi-density database is inaccurate. In addition, when it is used to cluster large databases, it will cost too much time. For these problems, we propose GMDBSCAN algorithm which is based on spatial index and grid technique. An experimental evaluation shows that GMDBSCAN is effective and efficient.

作者: Chen Xiaoyun Min Yufang Zhao Yan Wang Ping

作者单位: School of Information Science and Engineering, Lanzhou University Lanzhou 730000.PRC China School of Information Science and Engineering, Lanzhou University Lanzhou 30000.PRC China

会议类型: 国际会议

会议名称: AiR08，EM2108，SOAIC08，SIOKM08，BIMA08，DKEEE08(2008IEEE国际电子商务工程学术会议)

会议地点: 西安

会议语种:英文

页码: 780-783

在线出版日期: 2008-10-22（万方平台首次上网日期，不代表论文的发表时间）