The Application Of Clustering In Security Company

As the computers have been used in many fields, companies have accumulateda large number of row data. They are saved in DataBase. How to abstract knowledgefrom these data is the key task of Data mining technology. In this article we willapply clustering method on security company's data. Through analyzing we canknow many things from history information. This knowledge is the guide ofcompany's developing direction. First we discuss the background of data mining and some methods of it. Webriefly illustrate the basic of data warehouse and OLAP systems. They are thebasements of data mining. Second we will introduce the principle of clustering technology, which is oneof import method in data mining field. These clustering methods content fourcategories: partitioning method, hierarchical method, density-based method andgrid-base method. We present some representative algorithms of them. In additionwe discuss the present and future of clustering method The emphasis of this article is using GDBSCAN, one of density-basedclustering method to analyze the data of Security Company. The algorithm candiscover arbitrary shape clusters and can distinguish noise. A data structure called Xtree is choosing to speedup the algorithm. The X tree also makes it efficient at highdimension. The runtime complexity of GDBSCAN is O(nlogn). In the end we will demonstrates the using of GDBSCAN in Security Company.The importance of data mining using in security's field is showed. We chose asecurity company as an example. The architecture of it will be shown. Then we use aclustering session to show the whole produce of data mining.