Consumer contracts too often present clauses that are potentially unfair to the subscriber. We present an experimental study where machine learning is employed to automatically detect such potentially unfair clauses in online contracts. Results show that the proposed system could provide a valuable tool for lawyers and consumers alike.

Automated detection of unfair clauses in online consumer contracts / Lippi, M.; Palka, P.; Contissa, G.; Lagioia, F.; Micklitz, H. -W.; Panagis, Y.; Sartor, G.; Torroni, P.. - 302:(2017), pp. 145-154. (Intervento presentato al convegno 30th International Conference on Legal Knowledge and Information Systems, JURIX 2017 tenutosi a Kirchberg Campus of the University of Luxembourg, lux nel 2017) [10.3233/978-1-61499-838-9-145].

Automated detection of unfair clauses in online consumer contracts

Lippi M.;
2017

Abstract

Consumer contracts too often present clauses that are potentially unfair to the subscriber. We present an experimental study where machine learning is employed to automatically detect such potentially unfair clauses in online contracts. Results show that the proposed system could provide a valuable tool for lawyers and consumers alike.
2017
30th International Conference on Legal Knowledge and Information Systems, JURIX 2017
Kirchberg Campus of the University of Luxembourg, lux
2017
302
145
154
Lippi, M.; Palka, P.; Contissa, G.; Lagioia, F.; Micklitz, H. -W.; Panagis, Y.; Sartor, G.; Torroni, P.
Automated detection of unfair clauses in online consumer contracts / Lippi, M.; Palka, P.; Contissa, G.; Lagioia, F.; Micklitz, H. -W.; Panagis, Y.; Sartor, G.; Torroni, P.. - 302:(2017), pp. 145-154. (Intervento presentato al convegno 30th International Conference on Legal Knowledge and Information Systems, JURIX 2017 tenutosi a Kirchberg Campus of the University of Luxembourg, lux nel 2017) [10.3233/978-1-61499-838-9-145].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1215127
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