Taking email to task: the design and evaluation of a task management centered email tool
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Robustness of adaptive filtering methods in a cross-benchmark evaluation
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Email overload at work: an analysis of factors associated with email strain
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Vio: a mixed-initiative approach to learning and automating procedural update tasks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Quality versus quantity: e-mail-centric task management and its relation with overload
Human-Computer Interaction
Evaluation of an integrated multi-task machine learning system with humans in the loop
PerMIS '07 Proceedings of the 2007 Workshop on Performance Metrics for Intelligent Systems
Summarizing non-textual events with a 'briefing' focus
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
Learning user preferences in distributed calendar scheduling
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
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Email clients were not designed to serve as a task management tools, but a high volume of task-relevant information in email leads many people to use email clients for this purpose. Such usage aggravates a user's experience of email overload and reduces productivity. Prior research systems have sought to address this problem by experimentally adding task management capabilities to email client software. RADAR (Reflective Agents with Distributed Adaptive Reasoning) takes a different approach in which a software agent acts like a trusted human assistant. Many RADAR components employ machine learning to improve their performance. Human participant studies showed a clear impact of learning on useI peIformance metrics.