Name
Abstract | ||
|---|---|---|
Many real-world e-service applications require analyzing large volumes of transaction data to extract web access information. This paper describes Web Access Visualization (WAV) a system that visually associates the affinities and relationships of clients and URLs for large volumes of web transaction data. To date, many practical research projects have shown the usefulness of a physics-based mass-spring technique to layout data items with close relationships onto a graph. The WAV system: (1) maps transaction data items (clients, URLs) and their relationships to vertices, edges, and positions on a 3D spherical surface; (2) encapsulates a physics-based engine in a visual data analysis platform; and (3) employs various content sensitive visual techniques - linked multiple views, layered drill-down, and fade in/out - for interactive data analysis. We have applied this system to a web application to analyze web access patterns and trends. The web service quality has been greatly benefited from using the information provided by WAV. |
Year | Venue | Field |
|---|---|---|
2002 | VisSym | Static web page,Web mining,Web page,Web mapping,Computer science,Data Web,Web modeling,Web navigation,Web service,Database |
DocType | ISBN | Citations |
Conference | 1-58113-536-X | 2 |
PageRank | References | Authors |
0.38 | 10 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ming C. Hao | 1 | 2 | 0.38 |
| Pankaj Garg | 2 | 308 | 49.93 |
| Umeshwar Dayal | 3 | 8452 | 2538.92 |
| Vijay Machiraju | 4 | 330 | 36.67 |
| Daniel Cotting | 5 | 219 | 12.43 |