Visualization of Large Web Access Data Sets

Hao, Ming C.; Garg, Pankaj; Dayal, Umeshwar; Machiraju, Vijay; Cotting, Daniel

Visualization of Large Web Access Data Sets

Files

201-204.pdf (100.84 KB)

Date

2002

Authors

Hao, Ming C.
Garg, Pankaj
Dayal, Umeshwar
Machiraju, Vijay
Cotting, Daniel

Publisher

The Eurographics Association

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.

        @inproceedings{:10.2312/VisSym/VisSym02/201-204
,
booktitle = {Eurographics / IEEE VGTC Symposium on Visualization
},
editor = {D. Ebert and P. Brunet and I. Navazo
},
title = {{Visualization of Large Web Access Data Sets
}},
author = {Hao, Ming C. and 
Garg, Pankaj and 
Dayal, Umeshwar and 
Machiraju, Vijay and 
Cotting, Daniel
},
year = {2002
},
publisher = {The Eurographics Association
},
ISSN = {1727-5296
},
ISBN = {1-58113-536-X
},
DOI = {/10.2312/VisSym/VisSym02/201-204
}
}