Visualization of Large Web Access Data Sets
| dc.contributor.author | Hao, Ming C. | en_US |
| dc.contributor.author | Garg, Pankaj | en_US |
| dc.contributor.author | Dayal, Umeshwar | en_US |
| dc.contributor.author | Machiraju, Vijay | en_US |
| dc.contributor.author | Cotting, Daniel | en_US |
| dc.contributor.editor | D. Ebert and P. Brunet and I. Navazo | en_US |
| dc.date.accessioned | 2014-01-30T06:50:45Z | |
| dc.date.available | 2014-01-30T06:50:45Z | |
| dc.date.issued | 2002 | en_US |
| dc.description.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. | en_US |
| dc.description.seriesinformation | Eurographics / IEEE VGTC Symposium on Visualization | en_US |
| dc.identifier.isbn | 1-58113-536-X | en_US |
| dc.identifier.issn | 1727-5296 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/VisSym/VisSym02/201-204 | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.title | Visualization of Large Web Access Data Sets | en_US |
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