TaskTracer: a desktop environment to support multi-tasking knowledge workers
Abstract
This paper reports on TaskTracer --- a software system being designed to help highly multitasking knowledge workers rapidly locate, discover, and reuse past processes they used to successfully complete tasks. The system monitors users' interaction with a computer, collects detailed records of users' activities and resources accessed, associates (automatically or with users' assistance) each interaction event with a particular task, enables users to access records of past activities and quickly restore task contexts. We present a novel Publisher-Subscriber architecture for collecting and processing users' activity data, describe several different user interfaces tried with TaskTracer, and discuss the possibility of applying machine learning techniques to recognize/predict users' tasks.
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Previous approaches such as TaskTracer, Scalable Fabric, GroupBar and Mylyn allow the capturing and presentation of task context but require the user to manually group related artifacts or manually state the start and end of a task, reducing chances of long-term adoption.
“While previous approaches, such as TaskTracer [7], Scalable Fabric [78], GroupBar [9] and Mylyn [6], allow the capturing and presentation of task context, they require the user to manually group related artifacts or manually state the start and end of a task, thus, reducing chances of long-term adoption.”
From Detecting Developers' Task Switches and Types (2022) · cites this paper as [7]
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Gyllstrom, K., Soules, C. A. N., & Veitch, A. (2008) · Information Interaction in Context Symposium (IIiX) · doi:10.1145/1414694.1414707 · Cited by 14 · see citing works
Intelligent tutoring system for CS-I and II laboratory
Yoo, J. P., Pettey, C. C., Yoo, S., Hankins, J., Li, C., & Seo, S. J. (2006) · ACM Southeast Regional Conference (ACMSE) · doi:10.1145/1185448.1185482 · Cited by 13 · see citing works
Fuzzy Decision Tree for User Modeling from Human-Computer Interactions
Damez, M., Dang, T. H., Marsala, C., & Bouchon‐Meunier, B. (2005) · HAL · Cited by 13 · see citing works
Brdiczka, O. (2010) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/1719970.1720012 · Cited by 12 · see citing works
Personal Information Management: The Case for an Evolutionary Approach
Warren, P. (2013) · Interacting with Computers · doi:10.1093/iwc/iwt034 · Cited by 12 · see citing works
Automatically detecting developer activities and problems in software development work
Roehm, T., & Maalej, W. (2012) · doi:10.5555/2337223.2337390 · Cited by 12 · see citing works
Exploring the Effectiveness of Time-lapse Screen Recording for Self-Reflection in Work Context
Hu, D., & Lee, S. W. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642469 · Cited by 11 · see citing works
Tashman, C. S., & Edwards, W. K. (2012) · ACM Transactions on Computer-Human Interaction · doi:10.1145/2147783.2147791 · Cited by 11 · see citing works
Efficient online learning and prediction of users' desktop actions
Madani, O., Bui, H., & Yeh, E. (2009) · Cited by 11 · see citing works
Synergizing Standard and Ad-Hoc Processes
Rath, A., Kröll, M., Andrews, K., Lindstaedt, S., Granitzer, M., & Tochtermann, K. (2006) · Lecture notes in computer science · doi:10.1007/11944935_24 · Cited by 11 · see citing works
A Computational Decision Theory for Interactive Assistants
Fern, A., & Tadepalli, P. V. (2010) · Cited by 10 · see citing works
- Authors
- Dragunov, A. N., Dietterich, T. G., Johnsrude, K., McLaughlin, M., Li, L., & Herlocker, J. L.
- Affiliations
- Oregon State University (US)
- Venue
- Proceedings of the 10th international conference on Intelligent user interfaces
- Publisher
- ACM
- Published
- 2005-01-10
- Pages
- 75-82
- OpenAlex
- W2144266514
- Cited by
- 240
- References
- 22
- Citations by year
- 2026: 6 · 2025: 1 · 2024: 4 · 2023: 2 · 2022: 4 · 2021: 3 · 2020: 6 · 2019: 7 · 2018: 3 · 2017: 7 · 2016: 7 · 2015: 6 · 2014: 7 · 2013: 16 · 2012: 17
- FWCI
- 38.92
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM International Conference on Intelligent User Interfaces (IUI) (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Personal Information Management and User Behavior
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- knowledge workers, multitasking, process reuse, user activity monitoring, user interface, task identification, task prediction, machine learning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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