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Building a Vietnamese SentiWordNet Using Vietnamese Electronic Dictionary and String Kernel

机译:使用越南电子词典和字符串内核构建越南语SentiWordNet

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In this paper, we propose a novel approach to construct a Vietnamese SentiWordNet (VSWN), a lexical resource supporting sentiment analysis in Vietnamese. A SentiWordNet is typically generated from WordNet in which each synset has numerical scores to indicate its opinion polarities. However, Vietnamese WordNet is not yet available currently. Therefore, we propose a method to construct a VSWN from a Vietnamese electronic dictionary, not from WordNet. The main drawback of constructing a VSWN from a dictionary is that it is easy to suffer from the sparsity problem, since the glosses in the dictionary are short in general. As a solution to this problem, we adopt a string kernel function which measures the string similarity based on both common contiguous and non-contiguous subsequences. According to our experimental results, first, the use of string kernel outperforms a baseline model which uses the standard bag-of-word kernel. Second, the Vietnamese SentiWordNet is competitive with the English SentiWordNet which uses WordNet when it constructed. All those results prove that our methodology is effective and efficient in constructing a SentiWordNet from an electronic dictionary.
机译:在本文中,我们提出了一种新颖的方法来构建越南语SentiWordNet(VSWN),这是一种支持越南语中情感分析的词汇资源。 SentiWordNet通常是从WordNet生成的,其中每个同义词集都有数字分数,以表示其观点极性。但是,越南语WordNet当前尚不可用。因此,我们提出了一种从越南电子词典而不是从WordNet构建VSWN的方法。由字典构造VSWN的主要缺点是,由于字典中的光泽通常较短,因此很容易遭受稀疏性问题的困扰。为了解决这个问题,我们采用了一个字符串核函数,该函数基于共同的连续子序列和非连续子序列来测量字符串的相似性。根据我们的实验结果,首先,字符串内核的使用性能优于使用标准词袋内核的基线模型。其次,越南语SentiWordNet与英语SentiWordNet相比具有竞争优势,后者在构建时使用WordNet。所有这些结果证明,我们的方法在从电子词典构建SentiWordNet方面是有效且高效的。

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