Statute recommendation: Re-ranking statutes by modeling case-statute relation with interpretable hand-crafted features

نویسندگان

چکیده

In the continental law system, it is appropriate for judges to find relevant laws and consider rules defined in them when dealing with legal cases. Therefore, recommending quickly accurately based on case content crucial improving efficiency of processing. There have been researched works recommender systems various fields, but few lucubrates that recommend statutes To best our knowledge, there no research by modeling relationship between interpretable hand-crafted features. this paper, we define five novel types features calculating relevance a statute resorting all retrieved through collaborative filtering input case. Both pair-wise list-wise ranking models are trained these re-ranking list. Besides, also test combinations different learning algorithms popular pre-trained language models. Experimental results show adopting proposed achieves performance. It improves recommendation recall Top 1 almost 5% compared approach.

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ژورنال

عنوان ژورنال: Information Sciences

سال: 2022

ISSN: ['0020-0255', '1872-6291']

DOI: https://doi.org/10.1016/j.ins.2022.06.042