Predicting outcomes of web navigation

Authors:
Jacek Gwizdka;Ian Spence
Affiliations:
University of Toronto, Toronto, Canada;University of Toronto, Toronto, Canada
Venue:
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Year:
2005

Citing 5
Cited 1

Structural analysis of hypertexts: identifying hierarchies and useful metrics

ACM Transactions on Information Systems (TOIS)
Graphic and numerical methods to access navigation in hypertext

International Journal of Human-Computer Studies
A taxonomic analysis of what world wide web activities significantly impact people's decisions and actions

CHI '01 Extended Abstracts on Human Factors in Computing Systems
Clustering Web Sessions by Sequence Alignment

DEXA '02 Proceedings of the 13th International Workshop on Database and Expert Systems Applications
Mining longest repeating subsequences to predict world wide web surfing

USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2

Dweb model: Representing Web 2.0 dynamism

Computer Communications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Two exploratory studies examined the relationships among web navigation metrics, measures of lostness, and success on web navigation tasks. The web metrics were based on counts of visits to web pages, properties of the web usage graph, and similarity to an optimal path. Metrics based on similarity to an optimal path were good predictors of lostness and task success.