Intelligent email: reply and attachment prediction

  • Authors:
  • Mark Dredze;Tova Brooks;Josh Carroll;Joshua Magarick;John Blitzer;Fernando Pereira

  • Affiliations:
  • University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA

  • Venue:
  • Proceedings of the 13th international conference on Intelligent user interfaces
  • Year:
  • 2008

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Abstract

We present two prediction problems under the rubric of Intelligent Email that are designed to support enhanced email interfaces that relieve the stress of email overload. Reply prediction alerts users when an email requires a response and facilitates email response management. Attachment prediction alerts users when they are about to send an email missing an attachment or triggers a document recommendation system, which can catch missing attachment emails before they are sent. Both problems use the same underlying email classification system and task specific features. Each task is evaluated for both single-user and cross-user settings.