AAAI Publications, Third International AAAI Conference on Weblogs and Social Media

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Regression-Based Summarization of Email Conversations
Jan Ulrich, Giuseppe Carenini, Gabriel Murray, Raymond Ng

Last modified: 2009-07-07


In this paper we present a regression-based machine learning approach to email thread summarization. The regression model is able to take advantage of multiple gold-standard annotations for training purposes, in contrast to most work with binary classifiers.  We also investigate the usefulness of novel features such as speech acts. This paper also introduces a newly created and publicly available email corpus for summarization research.  We show that regression-based classifiers perform better than binary classifiers because they preserve more information about annotator judgements. In our comparison between different regression-based classifiers, we found that Bagging and Gaussian Processes have the highest weighted recall.


email; summarization; regression; machine learning; corpus

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