Post-Capitalist Society
Automated email activity management: an unsupervised learning approach
Proceedings of the 10th international conference on Intelligent user interfaces
TaskTracer: a desktop environment to support multi-tasking knowledge workers
Proceedings of the 10th international conference on Intelligent user interfaces
Communications of the ACM - The disappearing computer
Automatically classifying emails into activities
Proceedings of the 11th international conference on Intelligent user interfaces
A hybrid learning system for recognizing user tasks from desktop activities and email messages
Proceedings of the 11th 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
Using web browser interactions to predict task
Proceedings of the 15th international conference on World Wide Web
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Meeting of the MINDS: an information retrieval research agenda
ACM SIGIR Forum
A survey on context-aware systems
International Journal of Ad Hoc and Ubiquitous Computing
Task detection for activity-based desktop search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Human-Computer Interaction
Context as a dynamic construct
Human-Computer Interaction
Real-time detection of task switches of desktop users
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Enhancing just-in-time e-learning through machine learning on desktop context sensors
CONTEXT'07 Proceedings of the 6th international and interdisciplinary conference on Modeling and using context
Activity-centric support for weakly-structured business processes
Proceedings of the 2nd ACM SIGCHI symposium on Engineering interactive computing systems
Studying the factors influencing automatic user task detection on the computer desktop
EC-TEL'10 Proceedings of the 5th European conference on Technology enhanced learning conference on Sustaining TEL: from innovation to learning and practice
Automatic detection of accommodation steps as an indicator of knowledge maturing
Interacting with Computers
Rainbow of computer science
Towards a formalization of individual work execution at computer workplaces
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
Evaluation of social media collaboration using task-detection methods
EC-TEL'11 Proceedings of the 6th European conference on Technology enhanced learning: towards ubiquitous learning
Attention please!: learning analytics for visualization and recommendation
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Task-Based user modelling for knowledge work support
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Evaluating the student activity meter: two case studies
ICWL'11 Proceedings of the 10th international conference on Advances in Web-Based Learning
Ontology-based standardization on knowledge exchange in social knowledge management environments
Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies
Interaction history visualization
Proceedings of the 30th ACM international conference on Design of communication
Real-time task recognition based on knowledge workers' computer activities
Proceedings of the 30th European Conference on Cognitive Ergonomics
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'Understanding context is vital' [1] and 'context is key' [2] signal the key interest in the context detection field. One important challenge in this area is automatically detecting the user's task because once it is known it is possible to support her better. In this paper we propose an ontology-based user interaction context model (UICO) that enhances the performance of task detection on the user's computer desktop. Starting from low-level contextual attention meta-data captured from the user's desktop, we utilize rule-based, information extraction and machine learning approaches to automatically populate this user interaction context model. Furthermore we automatically derive relations between the model's entities and automatically detect the user's task. We present evaluation results of a large-scale user study we carried out in a knowledge-intensive business environment, which support our approach.