Google Tech TalksJuly 25, 2008ABSTRACTToday many workers find themselves caught between (a) a message centric world of email filled with natural language and (b) the form and report centric world of IT systems filled with structured information. Workers spend many hours navigating interfaces in order to complete tedious update and retrieval tasks to connect these worlds together. For example, an office assistant will be asked via email to book a trip to Paris. First he will retrieve information needed for the task, such as frequent flyer account numbers and approved corporate hotels. Then he will use the e-mail and retrieved information to complete the task. Fortunately, the repetitive nature of many of these tasks makes them ripe for automation using machine learning.This talk will detail the design and evaluation of VIO, a system that extracts information from email, automating update tasks. VIO monitors emails and makes task suggestions. VIO allows users to quickly identify and repair any suggestion errors, improving the machine learning performance as it learns to automate tasks. The talk will also share more recent work on MIXER, an interface that allows users to automate retrieval tasks triggered by incoming email messages. Once created, MIXER will augment an incoming email with the retrieved information needed to complete the task. Our initial evaluation demonstrates that this user-constructed agent can significantly reduce task completion time, freeing workers from mundane tasks.Speaker: Anthony TomasicAnthony Tomasic is the Director of the Carnegie Mellon University Master of Science in Information Technology, Very Large Information Systems (VLIS) program. His research currently focuses on applying machine learning to the desktop as part of the Carnegie Mellon University RADAR research program. Anthony has also published research on internet scale database systems, federated databases, and the performance of information retrieval systems. He has worked at Stanford University and INRIA (Rocquencourt). He received his Ph.D. in 1994 from Princeton University.
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