A Clustering Algorithm for Network Objects with Direction Factors
TANG Liang1,2,3, FANG Ting-Jian1,3
1.Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031 2.Department of Automation, University of Science and Technology of China, Hefei 230026 3.Research Center for ITS Engineering Technology of Anhui Province, Hefei 230088
Abstract:Clustering methods are analyzed in which Euclidean distance and network distance are used as a similarity measure respectively. The neighbor correlation between objects on a spatial network is discussed and a clustering algorithm is proposed for network objects with consideration of direction factors. The algorithm combines the two distances as the similarity measure of clustering by using the neighbor correlation. The analysis and experimental results indicate that the effectiveness of the proposed algorithm is better than those only using one measure.
[1] Qian Weining, Zhou Aoying. Analyzing Popular Clustering Algorithms from Different Viewpoints. Journal of Software, 2002, 13(8): 1382-1394 (in Chinese) (钱卫宁,周傲英.从多角度分析现有聚类算法. 软件学报, 2002, 13(8): 1382-1394) [2]Xu R, Wunsch I D. Survey of Clustering Algorithms. IEEE Trans on Neural Networks, 2005, 16(3): 645-678 [3]Han J, Kamber M. Data Mining Concepts and Techniques. 2nd Edition. Orlando, USA: Morgan Kaufmann, 2006 [4]Yiu M L, Mamoulis N. Clustering Objects on a Spatial Network // Proc of the ACM SIGMOD International Conference on Management of Data. Paris, France, 2004: 443-454 [5]Ester M, Kriegel H P, Sander J, et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise // Proc of the 2nd International Conference on Knowledge Discovery and Data Mining. Portland, USA, 1996: 226-231 [6] Chen Jidong, Meng Xiaofeng, Lai Caifeng. Clustering Objects in a Road Network. Journal of Software, 2007, 18(2): 332-344 (in Chinese) (陈继东,孟小峰,赖彩凤.基于道路网络的对象聚类.软件学报, 2007, 18(2): 332-344) [7] Agrawal R, Jagadish H. Algorithms for Searching Massive Graphs. IEEE Trans on Knowledge and Data Engineering, 1994, 6(2): 224-238