Modelling Topics of Car Accidents Events: A Text Mining Approach

Gabriele Cantaluppi () and Diego Zappa ()
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Gabriele Cantaluppi: Università Cattolica del Sacro Cuore
Diego Zappa: Università Cattolica del Sacro Cuore

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2021, pp 117-122 from Springer

Abstract: Abstract Car accident causes are relevant both for insurance companies as well as for policy makers. The former are interested into the dynamics of the accidents in order to evaluate responsibilities, the latter to foster good driving behavior for the sake of social benefit, too. By using a large set of medical and police reports, and by exploiting Natural Language Processing techniques we aim at grasping latent information useful to classify them according to the relevance of their content.

Keywords: Natural language processing; Text mining; Policy premiums (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-78965-7_18

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DOI: 10.1007/978-3-030-78965-7_18

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