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Word Similarity Computing Based on Hybrid Hierarchical Structure by HowNet

机译:知网基于混合层次结构的词相似度计算

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摘要

Word similarity computing is one of the most important and fundamental task in the field of natural language processing. Most of word similarity methods perform well in synonyms, but not well between words whose similarity is vague. It confronts the challenge of how to overcome this problem. An approach is proposed to compute Chinese word similarity based on hybrid hierarchical structure by HowNet to achieve fine-grained similarity results. The experimental results prove that the method has a better effect on computing similarity of synonyms and antonyms including nouns, verbs and adjectives. In addition, it performs well and stably on standard data provided by SemEval 2012.
机译:单词相似度计算是自然语言处理领域中最重要和最基本的任务之一。大多数词相似性方法在同义词中表现良好,但是在相似性模糊的词之间表现不佳。它面临着如何克服这个问题的挑战。提出了一种基于知网的混合层次结构计算汉字相似度的方法,以实现细粒度的相似度结果。实验结果证明,该方法对计算名词,动词,形容词等同义词与反义词的相似度有较好的效果。此外,它在SemEval 2012提供的标准数据上表现良好且稳定。

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