Predicting User Tasks : I Know What You ’ re Doing !

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 is investigating 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 combines human-computer interaction and machine learning to assign each observed action (opening a file, saving a file, sending an email, cutting and pasting information, etc.) to a task for which it is likely being performed. In this paper we report on ways we have applied machine learning in this environment and lessons learned so far.

[1]  Mathias Bauer Generation of Alternative Decompositions for Plan Libraries , 2007 .

[2]  Liam Bannon,et al.  Evaluation and analysis of users' activity organization , 1983, CHI '83.

[3]  Austin Henderson,et al.  A multiple, virtual-workspace interface to support user task switching , 1986, CHI '87.

[4]  Paul Dourish,et al.  Presto: an experimental architecture for fluid interactive document spaces , 1999, TCHI.

[5]  Mark Ginsburg,et al.  A Lightweight Framework for Cross-Application User Monitoring , 2002, Computer.

[6]  David Gelernter,et al.  Lifestreams: a storage model for personal data , 1996, SGMD.

[7]  Jeffrey O. Kephart,et al.  MailCat: an intelligent assistant for organizing e-mail , 1999, AGENTS '99.

[8]  Brian D. Davison,et al.  Predicting Sequences of User Actions , 1998 .

[9]  Mary Czerwinski,et al.  The Task Gallery: a 3D window manager , 2000, CHI.

[10]  Victor Kaptelinin,et al.  UMEA: translating interaction histories into project contexts , 2003, CHI '03.

[11]  John F. Canny,et al.  GaP: a factor model for discrete data , 2004, SIGIR '04.

[12]  Thomas G. Dietterich,et al.  TaskTracer: a desktop environment to support multi-tasking knowledge workers , 2005, IUI.

[13]  Raymond J. Mooney,et al.  Changing the Rules: A Comprehensive Approach to Theory Refinement , 1990, AAAI.

[14]  Ian Smith,et al.  Taking email to task: the design and evaluation of a task management centered email tool , 2003, CHI '03.

[15]  Jeffrey O. Kephart,et al.  Incremental Learning in SwiftFile , 2000, ICML.