Empirically validated web page design metrics
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Statistical profiles of highly-rated web sites
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Usability Engineering
Web TANGO: towards automated comparison of information-centric web site designs
CHI '00 Extended Abstracts on Human Factors in Computing Systems
Proceedings of the 11th international conference on Intelligent user interfaces
Intro STATS
Using Multivariate Statistics (5th Edition)
Using Multivariate Statistics (5th Edition)
Search Engines: Information Retrieval in Practice
Search Engines: Information Retrieval in Practice
SPSS Survival Manual: A Step by Step Guide to Data Analysis Using SPSS for Windows Version 15
SPSS Survival Manual: A Step by Step Guide to Data Analysis Using SPSS for Windows Version 15
SPSS for Windows Step-by-Step: A Simple Guide and Reference, 15.0 Update
SPSS for Windows Step-by-Step: A Simple Guide and Reference, 15.0 Update
Effects of display configurations on document triage
INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction
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Our work explores an approach to learning types of usability concerns considered useful for the management of Web sites and to identifying usability concerns based on these learned models. By having one or more Web site managers rate a subset of pages in a site based on a number of usability criteria, we build a model that determines what automatically measurable characteristics are correlated to issues identified. To test this approach, we collected usability assessments from twelve students pursuing advanced degrees in the area of computer-human interaction. These students were divided into two groups and given different scenarios of use of a Web site. They assessed the usability of Web pages from the site, and their data was divided into a training set, used to find models, and a prediction set, used to evaluate the relative quality of models. Results show that the learned models predicted remaining data for one scenario in more categories of usability than did the single model found under the alternate scenario. Results also show how systems may prioritize usability problems for Web site managers by probability of occurrence rather than by merely listing pages that break specific rules, as provided by some current tools.