利用DBpedia进行web搜索结果聚类

Conference on Automated Knowledge Base Construction Pub Date : 2013-10-27 DOI:10.1145/2509558.2509574

M. Schuhmacher, Simone Paolo Ponzetto

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引用次数: 15

摘要

我们提出了一种知识丰富的Web搜索结果聚类方法，该方法利用开放域实体链接器的输出，以及在广泛覆盖的本体中编码的类型和主题概念。我们的结果表明，由于搜索结果片段的准确和紧凑的语义化，我们能够在此任务的基准数据集上实现具有竞争力的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Exploiting DBpedia for web search results clustering

We present a knowledge-rich approach to Web search result clustering which exploits the output of an open-domain entity linker, as well as the types and topical concepts encoded within a wide-coverage ontology. Our results indicate that, thanks to an accurate and compact semantification of the search result snippets, we are able to achieve a competitive performance on a benchmarking dataset for this task.

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Conference on Automated Knowledge Base Construction

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