A REAL-TIME C-V CLUSTERING ALGORITHM FOR WEB-MINING

作     者：Li Haiying Zhuang Zhenquan Li Bin Wan Ke (Dept. of Electronic S &T, University of Science and Technology of China, HeFei 230026) Li Haiying Zhuang Zhenquan Li Bin Wan Ke (Dept. of Electronic S &T, University of Science and Technology of China, HeFei 230026)

作者机构：Dept. of Electronic S &T University of Science and Technology of China HeFei 230026 

出 版 物：《Journal of Electronics(China)》 (电子科学学刊（英文版）)

年 卷 期：2002年第19卷第1期

页      面：71-75页

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by 973 National R&D Items(G1998030413)and Centurial Project of CAS 

主　　题：Clustering algorithm Characteristic-vector Vector degree of matching 

摘      要：In this letter, a real-time C-V (Characteristic-Vector) clustering algorithm is put forth to treat with vast action data which are dynamically collected from web site. The algorithm cites the concept of C-V to denote characteristic, synchronously it adopts two-value [0,1]input and self-definition vigilance parameter to design clustering-architecture. Vector Degree of Matching (VDM) plays a key role in the clustering algorithm, which determines the magnitude of typical characteristic. Making use of stability analysis, the classifications are confirmed to have reliably hierarchical structure when vigilance parameter shifts from 0.1 to 0.99. This non-linear relation between vigilance parameter and classification upper limit helps mining out representative classifications from net-users according to the actual web resource, then administering system can map them to web resource space to implement the intelligent configuration effectually and rapidly.