Why CSCW applications fail: problems in the design and evaluationof organizational interfaces
CSCW '88 Proceedings of the 1988 ACM conference on Computer-supported cooperative work
Extracting usability information from user interface events
ACM Computing Surveys (CSUR)
Task analysis meets prototyping: seeking seamless UI-development
CHI '99 Extended Abstracts on Human Factors in Computing Systems
UMEA: translating interaction histories into project contexts
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using the Experience Sampling Method to Evaluate Ubicomp Applications
IEEE Pervasive Computing
ACM Transactions on Computer-Human Interaction (TOCHI)
A diary study of task switching and interruptions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Scalable Fabric: flexible task management
Proceedings of the working conference on Advanced visual interfaces
Display time as implicit feedback: understanding task effects
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
TaskTracer: a desktop environment to support multi-tasking knowledge workers
Proceedings of the 10th international conference on Intelligent user interfaces
TAMODIA '04 Proceedings of the 3rd annual conference on Task models and diagrams
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
SWISH: semantic analysis of window titles and switching history
Proceedings of the 11th international conference on Intelligent user interfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using web browser interactions to predict task
Proceedings of the 15th international conference on World Wide Web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Understanding memory triggers for task tracking
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Large scale analysis of web revisitation patterns
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Introduction to Information Retrieval
Introduction to Information Retrieval
Plastic: a metaphor for integrated technologies
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Activity put in context: identifying implicit task context within the user's document interaction
Proceedings of the second international symposium on Information interaction in context
Re-framing the desktop interface around the activities of knowledge work
Proceedings of the 21st annual ACM symposium on User interface software and technology
THE WAY I SEE IT: Memory is more important than actuality
interactions - The Counterfeit You
Self-interruption on the computer: a typology of discretionary task interleaving
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Classification of tasks using machine learning
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
Improving Window Switching Interfaces
INTERACT '09 Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II
YouPivot: improving recall with contextual search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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When using the computer, each user has some notion that "these applications are important" at a given point in time. We term this subset of applications that the user values as high-utility applications. Identifying high-utility applications is a critical first step for Task Analysis, Time Management/Workflow analysis, and Interruption research. However, existing techniques fail to identify at least 57% of these applications. Our work directly associates measurable computer interaction (CPU consumption, window area, etc.) with the user's perceived application utility without identifying task. In this paper, we present an objective utility function that accurately predicts the user's subjective impressions of application importance, improving existing techniques by 53%. This model of computer usage is based upon 321 hours of real-world data from 22 users (both professional and academic). Unlike existing approaches, our model is not limited by a pre-existing set of applications or known tasks. We conclude with a discussion of the direct implications for improving accuracy in the fields of interruptions, task analysis, and time management systems.