Applying Natural Language Generation to Indicative Summarization
计算与语言
2007-05-23 v2
摘要
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.
引用
@article{arxiv.cs/0107019,
title = {Applying Natural Language Generation to Indicative Summarization},
author = {Min-Yen Kan and Kathleen R. McKeown and Judith L. Klavans},
journal= {arXiv preprint arXiv:cs/0107019},
year = {2007}
}
备注
8 pages, published in Proc. of 8th European Workshop on NLG