AUTOMATIC CONDENSATION OF ELECTRONIC PUBLICATIONS BY SENTENCE SELECTION
AUTOMATIC CONDENSATION OF ELECTRONIC PUBLICATIONS BY SENTENCE SELECTION
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DOI：
10.1016/0306-4573(95)00052-i
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发表时间：
1995-09-01
影响因子：
8.6
通讯作者：
RAU, LF
中科院分区：
文献类型：
--
作者：
BRANDOW, R;MITZE, K;RAU, LF
随着电子信息访问成为常态，以及可检索材料的种类增加，自动总结或压缩文本的方法将变得至关重要。本文描述了一个系统，执行独立于域的自动浓缩的新闻从一个大型商业新闻服务，包括41个不同的出版物，该系统进行了评估，对系统，浓缩相同的文章，只使用的第一部分的文本（铅），目标长度的摘要。三个长度的文章进行了评估，250份文件，两个系统，共1500个适合性判断。迄今为止，可能是最大的人机总结评估的结果是出乎意料的，基于线索的总结明显优于“智能”总结，可接受性评级超过90%，而74.4%。本文简要回顾了文献，详细说明了这些结果的影响，并解决了剩余的希望基于内容的摘要。我们希望这里提出的结果是有用的其他研究人员目前调查的可行性摘要通过句子选择语法。
As electronic information access becomes the norm, and the variety of retrievable material increases, automatic methods of summarizing or condensing text will become critical. This paper describes a system that performs domain-independent automatic condensation of news from a large commercial news service encompassing 41 different publications, This system was evaluated against a system that condensed the same articles using only the first portion of the texts (the lead), up to the target length of the summaries. Three lengths of articles were evaluated for 250 documents by both systems, totalling 1500 suitability judgements in all. The outcome of perhaps the largest evaluation of human vs machine summarization performed to date was unexpected, The lead-based summaries outperformed the ''intelligent'' summaries significantly, achieving acceptability ratings of over 90%, compared to 74.4%. This paper briefly reviews the literature, details the implications of these results, and addresses the remaining hopes for content-based summarization. We expect the results presented here to be useful to other researchers currently investigating the viability of summarization through sentence selection heuristics.