k-Nearest-Neighbor Network Based Data Clustering Algorithm
Jia Zheng, W Automobile · 2010
Data clustering is a hotspot in data mining area.Though there have been lots of data clustering algorithms now,the clustering accuracy of them is far from perfect.A structural similarity based network clustering algorithm (SSNCA) is proposed in this paper,which attempt to further improve the data clustering accuracy from the view of network clustering.The concrete solution scheme is that vector dataset for clustering is converted to a k-Nearest-Neigborhood network and SSNCA is used to cluster this network.Comparing SSNCA with the algorithms of c-Means and affinity propagation (AP),experimental result shows that the fitness value got by the proposed algorithm is a little worse than AP,but its clustering accuracy is obviously better than that of the other two algorithms.