The DOI matches its Crossref record; 21 of the 22 references it cites were found in a registry or an index.
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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“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]
Citations
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Metadata
- 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
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