Assessing the Cross-Market Generalization Capability of the CLAUDETTE System

被引：2
|
作者：
Jablonowska, Agnieszka [1 ]
Lagioia, Francesca [1 ,2 ]
Lippi, Marco [1 ,3 ]
Micklitz, Hans-Wolfgang [4 ]
Sartor, Giovanni [1 ,2 ]
Tagiuri, Giacomo [1 ,5 ]
机构：
[1] European Univ Inst, Law Dept, Fiesole, Italy
[2] Univ Bologna, CIRSFID Alma AI, Bologna, Italy
[3] Univ Modena & Reggio Emilia, DISMI, Reggio Emilia, Italy
[4] European Univ Inst, Robert Schuman Ctr, Fiesole, Italy
[5] Polish Acad Sci, PL-00901 Warsaw, Poland
来源：
LEGAL KNOWLEDGE AND INFORMATION SYSTEMS | 2021年 / 346卷
基金：
欧盟地平线“2020”;
关键词：
Unfair clause detection; machine learning; cross-market analysis; UNFAIR TERMS;
D O I：
10.3233/FAIA210318
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a study aimed at testing the CLAUDETTE system's ability to generalise the concept of unfairness in consumer contracts across diverse market sectors. The data set includes 142 terms of services grouped in five sub-sets: travel and accommodation, games and entertainment, finance and payments, health and well-being, and the more general others. Preliminary results show that the classifier has satisfying performance on all the sectors.
引用
收藏
页码：62 / 67
页数：6
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