RECKONition: a NLP-based system for Industrial Accidents at Work Prevention

TL;DR

RECKONition is an NLP-based system designed to analyze Italian textual data on industrial accidents, aiding in prevention by understanding patterns and extracting useful information from non-English datasets.

Contribution

The paper introduces RECKONition, a novel NLP system tailored for Italian industrial accident reports, enhancing data understanding and prevention strategies.

Findings

Effective processing of Italian accident reports

Ability to extract accident patterns and insights

Supports accident prevention efforts

Abstract

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.