TY - CHAP U1 - Konferenzveröffentlichung A1 - Hellwig, Michael A1 - Finck, Steffen A1 - Mootz, Thomas A1 - Ehe, Andreas A1 - Rein, Florian ED - Abraham, Ajith ED - Gandhi, Niketa ED - Hanne, Thomas ED - Hong, Tzung-Pei ED - Nogueira Rios, Tatiane ED - Ding, Weiping T1 - NLP for product safety risk assessment BT - Towards consistency evaluations of human expert panels T2 - 21st International Conference on Intelligent Systems Design and Applications (ISDA 2021). December 13–15 2021 N2 - Recent developments in the area of Natural Language Processing (NLP) increasingly allow for the extension of such techniques to hitherto unidentified areas of application. This paper deals with the application of state-of-the-art NLP techniques to the domain of Product Safety Risk Assessment (PSRA). PSRA is concerned with the quantification of the risks a user is exposed to during product use. The use case arises from an important process of maintaining due diligence towards the customers of the company OMICRON electronics GmbH. The paper proposes an approach to evaluate the consistency of human-made risk assessments that are proposed by potentially changing expert panels. Along the stages of this NLP-based approach, multiple insights into the PSRA process allow for an improved understanding of the related risk distribution within the product portfolio of the company. The findings aim at making the current process more transparent as well as at automating repetitive tasks. The results of this paper can be regarded as a first step to support domain experts in the risk assessment process. KW - Natural Language Processing KW - Product Safety Risk KW - Machine Learning Y1 - 2022 SN - 2367-3389 SS - 2367-3389 SN - 2367-3370 SS - 2367-3370 SN - 978-3-030-96308-8 SB - 978-3-030-96308-8 U6 - https://doi.org/10.1007/978-3-030-96308-8_24 DO - https://doi.org/10.1007/978-3-030-96308-8_24 SP - 266 EP - 276 S1 - 10 PB - Springer CY - Cham ER -