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 ...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.展开更多
Let T be a tree with matching number μ(T). In this paper we obtain the following result: If T has no perfect matchings, thenμ(T) is a lower bound for the number of nonzero Laplacian eigenvalues of T which are smalle...Let T be a tree with matching number μ(T). In this paper we obtain the following result: If T has no perfect matchings, thenμ(T) is a lower bound for the number of nonzero Laplacian eigenvalues of T which are smaller than 2.展开更多
基金Supported by 973 National R&D Items(G1998030413)and Centurial Project of CAS
文摘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.
基金This research is supported by Anhui provincial Natural Science Foundation, Natural Science Foundation of Department of Education of Anhui Province of China (2004kj027)the Project of Research for Young Teachers of Universities of Anhui Province of China (2003jql01)and the Project of Anhui University for Talents Group Construction.
文摘Let T be a tree with matching number μ(T). In this paper we obtain the following result: If T has no perfect matchings, thenμ(T) is a lower bound for the number of nonzero Laplacian eigenvalues of T which are smaller than 2.
