The TaskTracer system

Authors:
Simone Stumpf;Xinlong Bao;Anton Dragunov;Thomas G. Dietterich;Jon Herlockel;Kevin Johnsrude;Lida Li;JianQiang Shen
Affiliations:
School of Electrical Engineering, Oregon State University, Corvallis, OR;School of Electrical Engineering, Oregon State University, Corvallis, OR;School of Electrical Engineering, Oregon State University, Corvallis, OR;School of Electrical Engineering, Oregon State University, Corvallis, OR;School of Electrical Engineering, Oregon State University, Corvallis, OR;School of Electrical Engineering, Oregon State University, Corvallis, OR;School of Electrical Engineering, Oregon State University, Corvallis, OR;School of Electrical Engineering, Oregon State University, Corvallis, OR
Venue:
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Year:
2005

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Abstract

Knowledge workers spend the majority of their working hours processing and manipulating information. These users face continual costs as they switch between tasks to retrieve and create information. The TaskTracer project at Oregon State University investigates the possibilities of a desktop software system that will record in detail how knowledge workers complete tasks, and intelligently leverage that information to increase efficiency and productivity. Our approach assigns each observed user interface action to a task for which it is likely being performed. In this demonstration we show how we have applied machine learning in this environment.