Kittask Computational Models of Concept Similarity for the Estonian Language
Kittask Computational Models of Concept Similarity for the Estonian Language
复制标题
爱沙尼亚语概念相似性的 Kittask 计算模型
作者：
Claudia
本论文的目的是测试和比较爱沙尼亚语不同的相似度计算模型。模型对单词和概念相似性的预测通常与人类的预测进行比较。为了在模型的相似性估计和人类得分之间进行这样的比较，必须为爱沙尼亚语言创建一个适当的人类注释数据集。选择SimLex-999数据集翻译成爱沙尼亚语。该资源用于测试三类相似性计算模型：分布模型、语义网络和计算机视觉模型。本文的研究结果可用于评价未来的相似度模型。
The purpose of this thesis is to test and compare different computational models of similarity for the Estonian language. Models’ predictions for words and concepts similarity is usually compared against human predictions. To make such comparisons between models’ similarity estimates and human scores, a proper human annotated data set had to be created for the Estonian language. The SimLex-999 data set was chosen for translation into Estonian. This resource is used to test three families of computational models of similarity: distributional models, semantic networks and computer vision models. The results of this thesis can be used to evaluate future similarity models.
DOI：
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发表时间：
2000
期刊：
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影响因子：
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作者：
Dan Jurafsky;James H. Martin
通讯作者：
Dan Jurafsky;James H. Martin