The task of prison term prediction is to predict the term of penalty based on textual fact description for a certain type of criminal case.Recent advances in deep learning frameworks inspire us to propose a two-step m...The task of prison term prediction is to predict the term of penalty based on textual fact description for a certain type of criminal case.Recent advances in deep learning frameworks inspire us to propose a two-step method to address this problem.To obtain a better understanding and more specific representation of the legal texts,we summarize a judgment model according to relevant law articles and then apply it in the extraction of case feature from judgment documents.By formalizing prison term prediction as a regression problem,we adopt the linear regression model and the neural network model to train the prison term predictor.In experiments,we construct a real-world dataset of theft case judgment documents.Experimental results demonstrate that our method can effectively extract judgment-specific case features from textual fact descriptions.The best performance of the proposed predictor is obtained with a mean absolute error of 3.2087 months,and the accuracy of 72.54%and 90.01%at the error upper bounds of three and six months,respectively.展开更多
Fact‑finding,as the foundation of a judicial decision,has been an important consideration in China’s judicial reform.This study introduces the theory of evidence‑based information and falsification methods in the fac...Fact‑finding,as the foundation of a judicial decision,has been an important consideration in China’s judicial reform.This study introduces the theory of evidence‑based information and falsification methods in the fact‑finding procedure of criminal investigations and proposes a paradigm for fact‑finding using combined pairs of approaches:individual evidence examination and global analysis,the objective basis and subjective perception of fact‑finders,and methods of verification and falsification.The working procedure of the paradigm is illustrated with the objective of making a contribution to the improvement of the existing model of fact‑finding in the criminal justice process.展开更多
It is of great significance for witnesses to appear in court in criminal cases so as to safeguard the right of confrontation of the defendant and achieve judicial justice.However,the witnesses in criminal cases refuse...It is of great significance for witnesses to appear in court in criminal cases so as to safeguard the right of confrontation of the defendant and achieve judicial justice.However,the witnesses in criminal cases refuse to appear in court and only give written testimony,and this has become a long‑standing problem in the judicial practice of China.To solve this problem,the Criminal Procedure Law of China,amended and improved the system of the witness appearing in court in 2012.Nevertheless,if the underlying problems in the judicial system of China are not settled,the system of the witness appearing in court in criminal cases still cannot turn into practicable measures.展开更多
基金This work is supported in part by the National Key Research and Development Program of China under grants 2018YFC0830602 and 2016QY03D0501in part by the National Natural Science Foundation of China(NSFC)under grants 61872111,61732022 and 61601146.
文摘The task of prison term prediction is to predict the term of penalty based on textual fact description for a certain type of criminal case.Recent advances in deep learning frameworks inspire us to propose a two-step method to address this problem.To obtain a better understanding and more specific representation of the legal texts,we summarize a judgment model according to relevant law articles and then apply it in the extraction of case feature from judgment documents.By formalizing prison term prediction as a regression problem,we adopt the linear regression model and the neural network model to train the prison term predictor.In experiments,we construct a real-world dataset of theft case judgment documents.Experimental results demonstrate that our method can effectively extract judgment-specific case features from textual fact descriptions.The best performance of the proposed predictor is obtained with a mean absolute error of 3.2087 months,and the accuracy of 72.54%and 90.01%at the error upper bounds of three and six months,respectively.
基金The work is supported by Social Science Foundation of Hebei Province under Grant No.HB18FX023,entitled as The Working Principle and Methods in Fact‑Finding of Criminal Cases.
文摘Fact‑finding,as the foundation of a judicial decision,has been an important consideration in China’s judicial reform.This study introduces the theory of evidence‑based information and falsification methods in the fact‑finding procedure of criminal investigations and proposes a paradigm for fact‑finding using combined pairs of approaches:individual evidence examination and global analysis,the objective basis and subjective perception of fact‑finders,and methods of verification and falsification.The working procedure of the paradigm is illustrated with the objective of making a contribution to the improvement of the existing model of fact‑finding in the criminal justice process.
文摘It is of great significance for witnesses to appear in court in criminal cases so as to safeguard the right of confrontation of the defendant and achieve judicial justice.However,the witnesses in criminal cases refuse to appear in court and only give written testimony,and this has become a long‑standing problem in the judicial practice of China.To solve this problem,the Criminal Procedure Law of China,amended and improved the system of the witness appearing in court in 2012.Nevertheless,if the underlying problems in the judicial system of China are not settled,the system of the witness appearing in court in criminal cases still cannot turn into practicable measures.
