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In-Browser Summarisation: Generating Elaborative Summaries BiasedTowards the Reading Context

机译:浏览器内摘要:生成偏向阅读上下文的实验摘要

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We investigate elaborative summarisation, where the aim is to identify supplementary information that expands upon a key fact. We envisage such summaries being useful when browsing certain kinds of (hyper-)linked document sets, such as Wikipedia articles or repositories of publications linked by citations. For these collections, an elaborative summary is intended to provide additional information on the linking anchor text. Our contribution in this paper focuses on identifying and exploring a real task in which summarisation is situated, realised as an In-Browser tool. We also introduce a neighbourhood scoring heuristic as a means of scoring matches to relevant passages of the document. In a preliminary evaluation using this method, our summarisation system scores above our baselines and achieves a recall of 57% annotated gold standard sentences.
机译:我们研究详尽的摘要,目的是识别扩展在关键事实上的补充信息。我们设想这样的摘要在浏览某些类型的(超)链接的文档集时很有用,例如Wikipedia文章或通过引文链接的出版物的存储库。对于这些集合,详尽的摘要旨在提供有关链接锚文本的其他信息。我们在本文中所做的贡献集中在识别和探索摘要所在的实际任务中,并通过浏览器工具实现。我们还介绍了一种邻域评分启发法,作为对文档相关段落进行匹配评分的一种方法。在使用此方法进行的初步评估中,我们的汇总系统得分高于基线,并且召回了57%的带注释的金标准句子。

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