@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} }