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Named Entity Recognition in Information Security Domain for Russian

机译:信息安全领域中针对俄罗斯的命名实体识别

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In this paper we discuss the named entity recognition task for Russian texts related to cybersecurity. First of all, we describe the problems that arise in course of labeling unstructured texts from information security domain. We introduce guidelines for human annotators, according to which a corpus has been marked up. Then, a CRF-based system and different neural architectures have been implemented and applied to the corpus. The named entity recognition systems have been evaluated and compared to determine the most efficient one.
机译:在本文中,我们讨论了与网络安全相关的俄语文本的命名实体识别任务。首先,我们描述了在信息安全领域中标记非结构化文本时出现的问题。我们介绍了用于人类注释者的准则,根据该准则对语料库进行了标记。然后,基于CRF的系统和不同的神经体系结构已被实现并应用于语料库。已对命名实体识别系统进行了评估和比较,以确定最有效的一种。

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