Combining linguistic and machine learning techniques for email summarization

Authors:
Smaranda Muresan;Evelyne Tzoukermann;Judith L. Klavans
Affiliations:
Columbia University, New York, NY;Lucent Technologies, Murray Hill, NJ;Columbia University, New York, NY
Venue:
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Year:
2001

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Abstract

This paper shows that linguistic techniques along with machine learning can extract high quality noun phrases for the purpose of providing the gist or summary of email messages. We describe a set of comparative experiments using several machine learning algorithms for the task of salient noun phrase extraction. Three main conclusions can be drawn from this study: (i) the modifiers of a noun phrase can be semantically as important as the head for the task of gisting, (ii) linguistic filtering improves the performance of machine learning algorithms, (iii) a combination of classifiers improves accuracy.