Automated detection of unfair clauses in online consumer contracts

dc.contributor.author	LIPPI, Marco
dc.contributor.author	PALKA, Przemyslaw
dc.contributor.author	CONTISSA, Giuseppe
dc.contributor.author	LAGIOIA, Francesca
dc.contributor.author	MICKLITZ, Hans-Wolfgang
dc.contributor.author	PANAGIS, Yannis
dc.contributor.author	SARTOR, Giovanni
dc.contributor.author	TORRONI, Paolo
dc.date.accessioned	2020-10-09T12:45:42Z
dc.date.available	2020-10-09T12:45:42Z
dc.date.issued	2017
dc.identifier.citation	Adam WYNER and Giovanni CASINI (eds), Legal knowledge and information systems, Amsterdam : IOS Press, 2017, Frontiers in artificial intelligence and applications ; 302, pp. 145-154	en
dc.identifier.isbn	9781614998389
dc.identifier.isbn	9781614998372
dc.identifier.uri	https://hdl.handle.net/1814/68540
dc.description.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.	en
dc.format.mimetype	application/pdf	en
dc.language.iso	en	en
dc.publisher	IOS Press	en
dc.rights	info:eu-repo/semantics/openAccess	en
dc.title	Automated detection of unfair clauses in online consumer contracts	en
dc.type	Contribution to book	en
dc.identifier.doi	10.3233/978-1-61499-838-9-145