Legal Similar Case Retrieval (LSCR) is a critical application in legal Artificial Intelligence (AI). It involves retrieving the most relevant cases from legal case databases through query cases. Legal cases are semi-s...
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ISBN:
(数字)9798350359312
ISBN:
(纸本)9798350359329
Legal Similar Case Retrieval (LSCR) is a critical application in legal Artificial Intelligence (AI). It involves retrieving the most relevant cases from legal case databases through query cases. Legal cases are semi-structured documents characterized by long text sequences and high specialization. Existing approaches rely on pre-trained language models for retrieval. However, these methods are constrained by the length of text input, preventing them from fully comprehending cases, which results in poor retrieval performance. Knowledge Graph (KG) are a type of graph structure data with dense knowledge and clear logic, which can represent the criminal processes and relationships among characters within legal cases. Currently, the mainstream approach for handling KG remains Graph Neural Networks (GNNs). However, these methods are limited by message passing and are prone to over-smoothing problems in the process of aggregating node features. To address these issues, we propose a Legal similar case retrieval model that combines Graph representation learning with the Transformer, called LeGalFormer. Three encoding methods are introduced to incorporate the structural information of the graph into the Transformer architecture. We evaluate the model on a real legal dataset, and the experimental results show that LeGalFormer significantly enhances the model's understanding capacity and achieves state-of-the-art performance.
The divisibility and congruence of usual and generalized central trinomial coefficients have been extensively investigated. The present paper is devoted to analytic properties of these numbers. We show that usual cent...
In this paper,we study the trigonometric approximation problems of functions which belong to the Lipαclass,the Lip(ξ(t))class,and the W(L_(M)^(*);ξ(t))class in Orlicz spaces by using the tools Hölder inequalit...
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In this paper,we study the trigonometric approximation problems of functions which belong to the Lipαclass,the Lip(ξ(t))class,and the W(L_(M)^(*);ξ(t))class in Orlicz spaces by using the tools Hölder inequality in Orlicz spaces,the second mean value theorem for integrals,and(E,q)(C,α,β)means *** the same time,we give the corresponding degree of approximation.
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