Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/4538

Title

Identification of clusters in the web graph based on link topology

Author(s)

Huang, Xiaodi;  Lai, Wei

Abstract

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.

Publication type

Conference paper

Research centre

Swinburne University of Technology. School of Information Technology

Source

Proceedings of the 7th International Database Engineering and Applications Symposium (IDEAS'03), Hong Kong, China, 16-18 July 2003, pp. 123-128

Publication year

2003

Keyword(s)

Clustering;  Web Graph;  K-Nearest Neighbor

Publisher

Institute of Electrical and Electronics Engineers

Format

pp. 123-128

ISSN

1098-8068

Publisher URL

http://doi.ieeecomputersociety.org/10.1109/IDEAS.2003.1214919