MacSHAPA and the enterprise of exploratory sequential data analysis (ESDA)
International Journal of Human-Computer Studies
Eye tracking the visual search of click-down menus
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Intelligent analysis of user interactions with web applications
Proceedings of the 7th international conference on Intelligent user interfaces
The Psychology of Human-Computer Interaction
The Psychology of Human-Computer Interaction
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Cognitive strategies and eye movements for searching hierarchical computer displays
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The bloodhound project: automating discovery of web usability issues using the InfoScentπ simulator
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
What are you looking for?: an eye-tracking study of information usage in web search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Canonical subsets of image features
Computer Vision and Image Understanding
Developing process models as summaries of HCI action sequences
Human-Computer Interaction
Human-Computer Interaction
Automated eye-movement protocol analysis
Human-Computer Interaction
A user-tracing architecture for modeling interaction with the world wide web
Proceedings of the Working Conference on Advanced Visual Interfaces
On Computing Canonical Subsets of Graph-Based Behavioral Representations
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
| Hi-index | 0.02 |
While the collection of behavioral protocols has been common practice in human-computer interaction research for many years, the analysis of large protocol data sets is often extremely tedious and time-consuming, and automated analysis methods have been slow to develop. This paper proposes an automated method of protocol analysis to find canonical behaviors --- a small subset of protocols that is most representative of the full data set, providing a reasonable "big picture" view of the data with as few protocols as possible. The automated method takes advantage of recent algorithmic developments in computational vision, modifying them to allow for distance measures between behavioral protocols. The paper includes an application of the method to web-browsing protocols, showing how the canonical behaviors found by the method match well to sets of behaviors identified by expert human coders.