@article {15292,
	title = {Single-document and multi-document summarization techniques for email threads using sentence compression},
	journal = {Information Processing \& Management},
	volume = {44},
	year = {2008},
	month = {2008/07//},
	pages = {1600 - 1610},
	abstract = {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 email collection {\^a}{\texteuro}{\textquotedblleft} 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.},
	keywords = {Email summarization, Enron, Informal media, Sentence compression, Trimming},
	isbn = {0306-4573},
	doi = {10.1016/j.ipm.2007.09.007},
	url = {http://www.sciencedirect.com/science/article/pii/S0306457307001768},
	author = {Zajic, David and Dorr, Bonnie J and Jimmy Lin}
}
