Extracting usability information from user interface events
ACM Computing Surveys (CSUR)
Essential COM
Python Programming on WIN32
Python Essential Reference
An Agent Framework for Intranet Document Management
Autonomous Agents and Multi-Agent Systems
SGML Nets: Integrating Document and Workflow Modeling
HICSS '98 Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences - Volume 2
TaskTracer: a desktop environment to support multi-tasking knowledge workers
Proceedings of the 10th international conference on Intelligent user interfaces
SWISH: semantic analysis of window titles and switching history
Proceedings of the 11th international conference on Intelligent user interfaces
A Practical Activity Capture Framework for Personal, Lifetime User Modeling
UM '07 Proceedings of the 11th international conference on User Modeling
Proceedings of the 8th workshop on Aspects, components, and patterns for infrastructure software
Predicting task-specific webpages for revisiting
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
On improving application utility prediction
CHI '10 Extended Abstracts on Human Factors in Computing Systems
The CLOTHO project: predicting application utility
Proceedings of the 8th ACM Conference on Designing Interactive Systems
Revealed processes in knowledge management
WM'05 Proceedings of the Third Biennial conference on Professional Knowledge Management
Discovery and diagnosis of behavioral transitions in patient event streams
ACM Transactions on Management Information Systems (TMIS)
| Hi-index | 4.11 |
Users often shift among applications as they seek needed data, integrating new material into e-mail messages, memos, and other documents.Unfortunately, the only record of this activity is a series of newly created files.The authors propose a lightweight framework for rich monitoring of multiapplication client sessions that captures allcross-application activity. This framework enables complex analyses of how users access and create information, even when they do so using several applications in concert. Implemented in the Python programming language on the Windows platform,the framework provides the infrastructure for implementing techniques to assist individual and group knowledge tasks. Users can apply it to build understanding in two major ways: monitoring information resource usage and analyzing how people use applications and tools.