Computing That Serves

TaskTracker and CALO: Intelligent Assistants for the Desktop


Thursday, November 3, 2005 - 10:00am


Thomas Dietterich, Professor of Electrical Engineering and Computer Science at Oregon State University

Knowledge workers are multi-taskers.  Their work lives can be divided into multiple on-going projects or activities, and their time at the desktop interleaves work on these projects and activities.  However, existing desktop user interfaces do not have any notion of coherent projects or activities.  The TaskTracer system seeks to support these workers by organizing the files, folders, contact information, calendar appointments, and web sites (collectively known as resources") according to the activities that they support.  To use askTracer, the user defines a hierarchy of projects/activities and declares to TaskTracer what current task he/she is working on at each point in time.  TaskTracer instruments Microsoft Windows and standard office applications to gather data on the resources that are accessed by the user and associates them with the currently-declared task.  It then provides project-related assistance through (a) the TaskExplorer (which makes it easy for the user to return to previously-accessed resources) and (b) the FolderPredictor (which predicts the relevant folder for Open and SaveAs actions).  To reduce the need for the user to declare the current activity, we apply machine learning methods to predict the current activity of the user.

TaskTracer is a part of the much larger CALO project, whose goal is to build an integrated intelligent system for the computer desktop.  In addition to presenting TaskTracer, this talk will also discuss the goals and accomplishments of the CALO project and some of the machine learning opportunities and challenges it raises.


Dr. Dietterich (AB Oberlin College 1977; MS University of Illinois 1979; PhD Stanford University 1984) joined the Oregon State University faculty in January 1985.  In 1987, he was named a Presidential Young Investigator for the NSF.  In 1990, he published, with Dr. Jude Shavlik, the book entitled "Readings in Machine Learning", and he also served as the Technical Program Co-Chair of the National Conference on Artificial Intelligence (AAAI-90).  From 1992-1998 he held the position of Executive Editor of the journal Machine Learning.  The American Association for Artificial Intelligence named him a Fellow in 1994, and the Association for Computing Machinery did the same in 2003.  In 2000, he co-founded a new, free electronic journal: The Journal of Machine Learning Research.  He served as Technical Program Chair of the Neural Information Processing Systems (NIPS) conference in 2000 and General Chair in 2001.  He currently President of the International Machine Learning Society, a member of the DARPA Information Science and Technology Study Group, and he also serves on the Board of Trustees of the NIPS Foundation.