Cited by 241Personal Information Management and User BehaviorUsability and User Interface DesignContext-Aware Activity Recognition Systems

TaskTracer: a desktop environment to support multi-tasking knowledge workers

Dragunov, Anton N., Dietterich, Thomas G., Johnsrude, Kevin, McLaughlin, Matthew, Li, Lida, Herlocker, Jonathan L.·2005·Proceedings of the 10th international conference on Intelligent user interfaces

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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Crossref · 10.1145/1040830.1040855

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21 of 21 references verified0 citation errors · 0 not checkable

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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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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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