Towards Answer-Focused Summarization
Towards Answer-Focused Summarization
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走向以答案为中心的总结
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
Weiguo Fan
中科院分区：
文献类型：
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作者：
Harris Wu;Dragomir R. Radev;Weiguo Fan
_人们查询搜索引擎以找到互联网上各种问题的答案。如果搜索引擎可以接受自然语言问题作为查询，并提供包含这些问题答案的摘要，搜索成本将大大降低。我们引入了以提问者为中心的摘要的概念，它将联合收割机摘要和问答结合起来。我们开发了一套标准和性能指标，以评估answerFocused摘要。我们证明，由谷歌，当今最流行的搜索引擎，产生的摘要，可以在很大程度上提高问答。我们开发了一个基于邻近度的摘要抽取系统，然后利用问题类型，即问题是“人”还是“地方”的问题，以提高性能。我们认为，有一个很大的应用潜力，如在无线和掌上电脑系统中的搜索成本是至关重要的。
_ People query search engines to find answers to a variety of questions on the Internet. Search cost would have been greatly reduced if search engines could accept natural language questions as queries, and provide summaries that contain the answers to these questions. We introduce the notion of Answer-Focused Summarization, which is to combine summarization and question answering. We develop a set of criteria and performance metrics, to evaluate answerFocused Summarization. We demonstrate that the summaries produced by Google, the most popular search engine nowadays, can be largely improved for question answering. We develop a proximity-based summary extraction system, and then utilize question types, i.e. whether the question is a "person" or a "place" question, to improve the performance. We suggest that there is a large application potential for Answer-Focused Summarization, such as in wireless and palmheld systems where search cost is critical.