We address the problem of suggesting who to add as an additional recipient (i.e. cc, or carbon copy) for an email under composition. We address the problem using graphical models for words in the body and subject line of the email as well as the recipients given so far on the email. The problem of cc prediction is closely related to the problem of expert flnding in an organization. We show that graphical models present a variety of solutions to these problems. We present results using naively structured models and introduce a powerful new modeling tool: plated factor graphs.
['Christopher J. Pal', 'Andrew McCallum']
CC Prediction with Graphical Models