The Community for Technology Leaders
RSS Icon
Hong Kong, SAR
July 16, 2003 to July 18, 2003
ISBN: 0-7695-1981-4
pp: 123
Xiaodi Huang , Swinburne University of Technology
Wei Lai , Swinburne University of Technology
The web graph has recently been used to model the link structure of the Web. The studies of such graphs can yield valuable insights into web algorithms for crawling, searching and discovery of web communities. This paper proposes a new approach to clustering the Web graph. The proposed algorithm identifies a small subset of the graph as "core" members of clusters, and then incrementally constructs the clusters by a selection criterion. Two qualitative criteria are proposed to measure the quality of graph clustering. We have implemented our algorithm and tested a set of arbitrary graphs with good results. Applications of our approach include graph drawing and web visualization.
Clustering, Web Graph, K-Nearest Neighbor
Xiaodi Huang, Wei Lai, "Identification of Clusters in the Web Graph Based on Link Topology", IDEAS, 2003, Database Engineering and Applications Symposium, International, Database Engineering and Applications Symposium, International 2003, pp. 123, doi:10.1109/IDEAS.2003.1214919
18 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool