This paper presents the latest developments of the use of memory network models in detecting and explaining unfair terms in online consumer contracts. We extend the CLAUDETTE tool for the detection of potentially unfair clauses in online Terms of Service, by providing to the users the explanations of unfairness (legal rationales) for five different categories: Arbitration, unilateral change, content removal, unilateral termination, and limitation of liability.

Explaining potentially unfair clauses to the consumer with the Claudette tool / Liepina R.; Ruggeri F.; Lagioia F.; Lippi M.; Drazewski K.; Torroni P.. - ELETTRONICO. - 2645:(2020), pp. 61-64. (Intervento presentato al convegno SAE 2020 Automotive Technical Papers, WONLYAUTO 2020 tenutosi a usa nel 2020).

Explaining potentially unfair clauses to the consumer with the Claudette tool

Lippi M.;
2020

Abstract

This paper presents the latest developments of the use of memory network models in detecting and explaining unfair terms in online consumer contracts. We extend the CLAUDETTE tool for the detection of potentially unfair clauses in online Terms of Service, by providing to the users the explanations of unfairness (legal rationales) for five different categories: Arbitration, unilateral change, content removal, unilateral termination, and limitation of liability.
2020
CEUR Workshop Proceedings
SAE 2020 Automotive Technical Papers, WONLYAUTO 2020
usa
2020
Liepina R.; Ruggeri F.; Lagioia F.; Lippi M.; Drazewski K.; Torroni P.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1356525
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact