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Semantic similarity of short texts in languages with a deficient natural language processing support

机译:缺乏自然语言处理支持的语言中的短文本的语义相似性

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Measuring the semantic similarity of short texts is a noteworthy problem since short texts are widely used on the Internet, in the form of product descriptions or captions, image and webpage tags, news headlines, etc. This paper describes a methodology which can be used to create a software system capable of determining the semantic similarity of two given short texts. The proposed LlnSTSS approach is particularly suitable for application in situations when no large, publicly available, electronic linguistic resources can be found for the desired language. We describe the basic working principles of the system architecture we propose, as well as the stages of its construction and use. Also, we explain the procedure used to generate a paraphrase corpus which is then utilized in the evaluation process. Finally, we analyze the evaluation results obtained from a system created for the Serbian language, and we discuss possible improvements which would increase system accuracy.
机译:测量短文本的语义相似性是一个值得注意的问题,因为短文本以产品描述或标题,图像和网页标签,新闻标题等形式在Internet上得到广泛使用。本文介绍了一种可用于创建一个能够确定两个给定短文本的语义相似性的软件系统。所提出的LlnSTSS方法特别适用于找不到所需语言所需的大量公共可用电子语言资源的情况。我们描述了我们提出的系统体系结构的基本工作原理,以及其构建和使用的阶段。此外,我们解释了用于生成复述语料库的过程,然后将其用于评估过程。最后,我们分析了从针对塞尔维亚语言创建的系统中获得的评估结果,并讨论了可能会提高系统准确性的改进措施。

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