Extracting patterns and useful information from Natural Language datasets is a challenging task, especially when dealing with data written in a language different from English, like Italian. Machine and Deep Learning, together with Natural Language Processing (NLP) techniques have widely spread and improved lately, providing a plethora of useful methods to address both Supervised and Unsupervised problems on textual information. We propose RECKONition, a NLP-based system for Industrial Accidents at Work Prevention. RECKONition, which is meant to provide Natural Language Understanding, Clustering and Inference, is the result of a joint partnership with the Italian National Institute for Insurance against Accidents at Work (INAIL). The obtained results showed the ability to process textual data written in Italian describing industrial accidents dynamics and consequences.
翻译:从自然语言数据集中提取模式和有用信息是一项艰巨的任务,特别是在处理以不同于英语的语文编写的数据时,如意大利语。机器和深层学习技术以及自然语言处理技术最近已经广泛传播和改进,提供了大量有用的方法,以解决在文字信息方面受到监督和不受监督的问题。我们建议采用基于自然语言数据集的劳动事故预防系统RECKONIST。RECONIP旨在提供自然语言理解、集群和推断,这是与意大利国家工伤事故保险研究所(INAIL)联合合作的结果。获得的结果表明,能够处理意大利文中描述工业事故动态和后果的文字数据。