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Context Based Wikipedia Linking

机译:基于上下文的维基百科链接

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摘要

Automatically linking Wikipedia pages can be done either content based by exploiting word similarities or structure based by exploiting characteristics of the link graph. Our approach focuses on a content based strategy by detecting Wikipedia titles as link candidates and selecting the most relevant ones as links. The relevance calculation is based on the context, i.e. the surrounding text of a link candidate. Our goal was to evaluate the influence of the link-context on selecting relevant links and determining a links best-entry-point. Results show, that a whole Wikipedia page provides the best context for resolving link and that straight forward inverse document frequency based scoring of anchor texts achieves around 4% less Mean Average Precision on the provided data set.
机译:自动链接维基百科页面既可以通过利用单词相似性来实现基于内容的方式,也可以通过利用链接图的特征来实现的结构。我们的方法通过检测Wikipedia标题作为链接候选者并选择最相关的链接作为链接,从而着重于基于内容的策略。相关性计算基于上下文,即链接候选的周围文本。我们的目标是评估链接上下文对选择相关链接并确定链接最佳入口点的影响。结果表明,整个Wikipedia页面都为解析链接提供了最佳上下文,并且基于直接逆文档频率的锚文本评分在所提供的数据集上平均平均精度降低了约4%。

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