以维基百科为参考从文本中提取语义信息

Andrea Prato, M. Ronchetti
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引用次数: 3

摘要

本文提出了一种以维基百科为参考,从任意文本中提取语义信息的算法。我们的算法改进了其他人提出的一个程序,该程序挖掘了整个维基百科中包含的所有文本。我们的改进基于聚类方法,利用了某些类型的维基百科超链接中包含的语义信息,并引入了基于多词的分析。我们的算法优于当前的方法,因为输出包含更少的误报。我们还能够理解文本的哪个(结构)部分提供了算法提取的大部分语义信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Wikipedia as a Reference for Extracting Semantic Information from a Text
In this paper we present an algorithm that, using Wikipedia as a reference, extracts semantic information from an arbitrary text. Our algorithm refines a procedure proposed by others, which mines all the text contained in the whole Wikipedia. Our refinement, based on a clustering approach, exploits the semantic information contained in certain types of Wikipedia hyperlinks, and also introduces an analysis based on multi-words. Our algorithm outperforms current methods in that the output contains many less false positives. We were also able to understand which (structural) part of the texts provides most of the semantic information extracted by the algorithm.
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