Applying natural language generation to indicative summarization

Authors:
Min-Yen Kan;Kathleen R. McKeown;Judith L. Klavans
Affiliations:
Columbia University, New York, NY;Columbia University, New York, NY;Columbia University, New York, NY
Venue:
EWNLG '01 Proceedings of the 8th European workshop on Natural Language Generation - Volume 8
Year:
2001

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Abstract

The task of creating indicative summaries that help a searcher decide whether to read a particular document is a difficult task. This paper examines the indicative summarization task from a generation perspective, by first analyzing its required content via published guidelines and corpus analysis. We show how these summaries can be factored into a set of document features, and how an implemented content planner uses the topicality document feature to create indicative multidocument query-based summaries.