Detecting Collocations Similarity via Logical-Linguistic Model

N. Khairova, S. Petrasova, O. Mamyrbayev, Kuralay Mukhsina
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Abstract

Semantic similarity between collocations, along with words similarity, is one of the main issues of NLP, which must be addressed, in particular, in order to facilitate the automatic thesaurus generation. In the paper, we consider the logical-linguistic model that allows defining the relation of semantic similarity of collocations via the logical-algebraic equations. We provide the model for English, Ukrainian and Russian text corpora. The implementation for each language is slightly different in the equations of the finite predicates algebra and used linguistic resources. As a dataset for our experiment, we use 5801 pairs of sentences of Microsoft Research Paraphrase Corpus for English and more than 1 000 texts of scientific papers for Russian and Ukrainian.
基于逻辑语言模型的搭配相似度检测
搭配之间的语义相似度,以及词的相似度,是NLP的主要问题之一,必须加以解决,特别是为了促进自动生成同义词库。在本文中,我们考虑了允许通过逻辑代数方程来定义搭配的语义相似关系的逻辑语言模型。我们为英语、乌克兰语和俄语文本语料库提供了模型。每种语言的实现在有限谓词代数方程和使用的语言资源方面略有不同。作为我们实验的数据集,我们使用了微软研究意译语料库的5801对句子(英语)和1000多篇俄语和乌克兰语的科学论文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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