With the ever increasing popularity of emails, email over-load and prioritization becomes a major problem for many email users. Users spend a lot of time reading, replying and organizing their emails. To help users organize their email messages, we propose a new framework to help organised and prioritized email better; email reply prediction. The goal is to provide concise, highly structured and prioritized emails, thus saving the user from browsing through each email one by one and help to save time. In this paper, we discuss the features used to differentiate emails, show promising initial results with unsupervised machine learning model, and outline future directions for this work.
|Title of host publication
|Proceedings of the 3rd International Conference on Digital Information Management, ICDIM 2008
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 9 Jan 2009
|3rd International Conference on Digital Information Management, ICDIM 2008 - London, United Kingdom
Duration: 13 Nov 2008 → 16 Nov 2008
|3rd International Conference on Digital Information Management, ICDIM 2008
|13/11/08 → 16/11/08
- Email reply prediction
- Interrogative words
- Require reply