Plans and situated actions: the problem of human-machine communication
Plans and situated actions: the problem of human-machine communication
A visual calendar for scheduling group meetings
CSCW '90 Proceedings of the 1990 ACM conference on Computer-supported cooperative work
A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Portholes: supporting awareness in a distributed work group
CHI '92 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Groupware and social dynamics: eight challenges for developers
Communications of the ACM
Agents that reduce work and information overload
Communications of the ACM
Speech acts and voices: response to Winograd et al.
Computer Supported Cooperative Work
Satisfying user preferences while negotiating meetings
International Journal of Human-Computer Studies - Special issue: group support systems
Direct manipulation vs. interface agents
interactions
Machine Learning - Special issue on learning with probabilistic representations
Trust breaks down in electronic contexts but can be repaired by some initial face-to-face contact
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Social, individual and technological issues for groupware calendar systems
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Calendars on the new frontier: challenges of groupware technology
Calendars on the new frontier: challenges of groupware technology
SUPPLE: automatically generating user interfaces
Proceedings of the 9th international conference on Intelligent user interfaces
Examining the robustness of sensor-based statistical models of human interruptibility
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
IBM Systems Journal
Automated email activity management: an unsupervised learning approach
Proceedings of the 10th international conference on Intelligent user interfaces
Active preference learning for personalized calendar scheduling assistance
Proceedings of the 10th international conference on Intelligent user interfaces
Coordinate: probabilistic forecasting of presence and availability
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Preference-based group scheduling
INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction
The calendar is crucial: Coordination and awareness through the family calendar
ACM Transactions on Computer-Human Interaction (TOCHI)
Exposing parameters of a trained dynamic model for interactive music creation
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Event maps: a collaborative calendaring system for navigating large-scale events
CHI '10 Extended Abstracts on Human Factors in Computing Systems
"Luckily, I don't need it": elderly and the use of artifacts for time management
Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries
PTIME: Personalized assistance for calendaring
ACM Transactions on Intelligent Systems and Technology (TIST)
Proceedings of the 2013 conference on Computer supported cooperative work
Hi-index | 0.01 |
As our business, academic, and personal lives continue to move at an ever-faster pace, finding times for busy people to meet has become an art. One of the most perplexing challenges facing groupware is effective asynchronous group scheduling (GS). This paper presents a lightweight interaction model for GS that can extend its reach beyond users of current group calendaring solutions. By expressing availability in terms of preferences, we create a flexible framework for GS that preserves plausible deniability while exerting social pressure to encourage honesty among users. We also propose an ontology that enables us to model user preferences with machine learning, predicting user responses to further lower cognitive load. The combination of visualization/direct manipulation with machine learning allows users to easily and efficiently optimize meeting times. We also suggest resulting design implications for this class of intelligent user interfaces.