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Measuring Semantic Relatedness Between Two Wikipedia Articles

机译:测量两个维基百科文章之间的语义相关性

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This paper mainly focuses on estimating the relatedness and similarities between any two Wikipedia [1] articles. This paper describes various ways of determining the similarities. We hypothesize that by using some kind of properties of the Wikipedia articles, which can be internal or external, we can estimate the relatedness between Wikipedia articles. Each article is believed to have some kinds of internal properties and some external properties. Internal properties are those which are embedded inside the articles. It can be, for instance, have something to do with the content and text of the articles. External properties are those which are deduced or inferred from the articles. It can be, for example, the topic of the articles or even the closest distance between the two articles when plotted in a graph or in a category hierarchy. External properties include the properties associated with individual articles like topics (as mentioned), categories of the articles. Other techniques which are relevant when comparing the Wikipedia articles are cosine similarity, Jaccard similarity measure etc.
机译:本文主要集中在估计任意两篇Wikipedia [1]文章之间的相关性和相似性。本文介绍了确定相似性的各种方法。我们假设通过使用Wikipedia文章的某种属性(可以是内部的或外部的),我们可以估计Wikipedia文章之间的相关性。据信每种制品都具有某些内部特性和一些外部特性。内部属性是那些嵌入在文章内部的属性。例如,它可能与文章的内容和文本有关。外部属性是从文章中推论得出的那些属性。例如,它可以是文章的主题,甚至可以是图表或类别层次结构中两个文章之间最接近的距离。外部属性包括与各个文章相关联的属性,例如主题(如上所述),文章类别。比较Wikipedia文章时其他相关的技术是余弦相似度,Jaccard相似度度量等。

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