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FCA-LJP: A Method Based on Formal Concept Analysis for Case Judgment Prediction

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Abstract

In recent years, the field of intelligent justice has attracted a lot of academic attention. Among them, legal judgment prediction (LJP) is the most important research direction in the field of intelligent justice. LJP predict the results according to the facts of criminal cases and LJP is becoming a research hotspot in the legal realm. LJP mainly includes the following: (1) applicable law article prediction (2) charge prediction (3) term of penalty prediction. Most of the existing research methods are based on neural networks. Due to the characteristics of neural network, the interpretability of the final results is poor. In this paper, formal concept analysis (FCA) was introduced in the LJP task and a method called FCA-LJP was proposed. The original FCA method is improved based on the characteristics of the LJP task in order to make FCA-LJP more suitable the LJP task. The generalization and specialization of the formal concept used in FCA can find the common ground between different cases in the same charge. At last, we conduct experiments on the public data set of the Legal AI Challenge. The experimental results show that the FCA-LJP method has better prediction results.

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Acknowledgements

This research was supported by the Key Research Projects of Henan Higher Education Institutions (Grant No. 23A520026), the Technological Research of Key Projects of Henan Province (Grant Nos. 232102210032,232102240020), the Scientific and Technological Project of Henan Province (Grant No. 202102310340), and the Foundation of University Young Key Teacher of Henan Province (Grant Nos. 2019GGJS040, 2020GGJS027).

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Authors and Affiliations

  1. School of Computer and Information Engineering, Henan Key Laboratory of Big Data Analysis and Processing, Henan Province Engineering Research Center of Spatial Information Processing, Henan University, Kaifeng, 475004, China

    Lei Zhang, Feifei Zao & Xiaoding Guo

  2. Institute of Cyberspace Security, Harbin Institute of Technology, Harbin, 150001, China

    Zhuo Shen

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  1. Lei Zhang
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  2. Feifei Zao
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Correspondence to Xiaoding Guo.

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Zhang, L., Zao, F., Shen, Z. et al. FCA-LJP: A Method Based on Formal Concept Analysis for Case Judgment Prediction. Neural Process Lett 55, 10053–10072 (2023). https://doi.org/10.1007/s11063-023-11238-9

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