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An Approach for Word Categorization Based on Semantic Similarity Measure Obtained from Search Engines

机译:基于搜索引擎获得的语义相似度测量的字分类方法

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Word categorization based on semantic similarity is a problem need to be solved for several natural language applications. A similarity measure is need for word categorization. In this study it is proposed that the semantic similarity between two Turkish words is in direct proportion to the number of pages which the words are located next to each other. Google and Yahoo search engines were used to find the number of pages. In the first attempt to verify the proposal, the experiments were done with small datasets. The average success ratio is 87%.
机译:基于语义相似性的单词分类是需要解决几种自然语言应用程序的问题。相似度量是针对单词分类的。在这项研究中,提出了两个土耳其词之间的语义相似性与单词彼此相邻的页数直接比例。谷歌和雅虎搜索引擎被用来找到页数。在第一次尝试验证提案时,实验是用小型数据集完成的。平均成功比率为87%。

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