Applying Natural Language Generation to Indicative Summarization

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dc.creatorKan, Min-Yen
dc.creatorMcKeown, Kathleen R.
dc.creatorKlavans, Judith L.
dc.date2001-07-16
dc.date2001-07-16
dc.date.accessioned2026-07-07T03:17:21Z
dc.date.available2026-07-07T03:17:21Z
dc.descriptionThe 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.
dc.description8 pages, published in Proc. of 8th European Workshop on NLG
dc.identifierhttps://arxiv.org/abs/cs/0107019
dc.identifierhttp://arxiv.org/abs/cs/0107019
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30691
dc.subjectComputation and Language
dc.subjectI.2.7
dc.titleApplying Natural Language Generation to Indicative Summarization
dc.typetext

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