创建一个来自维基百科的短语相似图

L. Stanchev
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引用次数: 9

摘要

本文利用相似度图对英语短语之间的关系进行建模。数学模型存储以十进制数字表示的短语之间关系强度的数据。来自维基百科的结构化数据(例如标题为“狗”的维基百科页面属于维基百科类别“驯养动物”)和文本描述(例如标题为“狗”的维基百科页面包含“狼”这个词31次)都被用于创建图。通过使用我们的软件比较短语对的相似性来验证图形数据的质量,该软件使用图形与人类受试者进行的研究结果进行比较。据我们所知,我们的软件与米勒和查尔斯的研究以及wordsimilarity353的研究结果的相关性比其他任何已发表的研究都要好。
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Creating a Phrase Similarity Graph from Wikipedia
The paper addresses the problem of modeling the relationship between phrases in English using a similarity graph. The mathematical model stores data about the strength of the relationship between phrases expressed as a decimal number. Both structured data from Wikipedia, such as that the Wikipedia page with title "Dog" belongs to the Wikipedia category "Domesticated animals", and textual descriptions, such as that the Wikipedia page with title "Dog" contains the word "wolf" thirty one times are used in creating the graph. The quality of the graph data is validated by comparing the similarity of pairs of phrases using our software that uses the graph with results of studies that were performed with human subjects. To the best of our knowledge, our software produces better correlation with the results of both the Miller and Charles study and the WordSimilarity-353 study than any other published research.
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