Abstract
A Web graph refers to the graph that models the hyperlink relations between Web pages in the WWW, where a node represents a URL and an edge indicates a link between two URLs. A Web graph is normally a very huge graph. In the course of users' Web exploration, only part of the Web graph is displayed on the screen each time according to a user's current navigation focus. In this paper, we make use of a fast kernel-based algorithm that is able to cluster large graphs. The algorithm is implemented in an online visualization system of Web graphs. In the system, a Web crawler first generates the Web graph of web sites. The clustering algorithm then reduces the visual complexities of the large graph. In particular, it groups a set of highly connected nodes and their edges into a clustered graph with abstract nodes and edges. The experiments have demonstrated that the employed algorithm is able to cluster graphs
Original language | English |
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Title of host publication | CGIV 2007 |
Subtitle of host publication | Computer graphics, imaging and visualization: new advances |
Place of Publication | USA |
Publisher | IEEE |
Pages | 454-459 |
Number of pages | 6 |
ISBN (Electronic) | 0769526063 |
DOIs | |
Publication status | Published - 2007 |
Event | IEEE International Conference on Computer Graphics, Imaging and Visualisation (CGIV) - Bangkok, Thailand, Thailand Duration: 14 Aug 2007 → 17 Aug 2007 |
Conference
Conference | IEEE International Conference on Computer Graphics, Imaging and Visualisation (CGIV) |
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Country/Territory | Thailand |
Period | 14/08/07 → 17/08/07 |