We present two approaches to email thread summarization: Collective Message Summarization (CMS) applies a multi-document summarization approach, while Individual Message Summarization (IMS) treats the problem as a sequence of single-document summarization tasks. Both approaches are implemented in our general framework driven by sentence compression. Instead of a purely extractive approach, we employ linguistic and statistical methods to generate multiple compressions, and then select from those candidates to produce a final summary. We demonstrate these ideas on the Enron collection--a very challenging corpus because of the highly technical language. Experimental results point to two findings: that CMS represents a better approach to email thread summarization, and that current sentence compression techniques do not improve summarization performance in this genre.
David M. Zajic, Bonnie J. Dorr, Jimmy J. Lin