A method for predicting prison term based on multi-task artificial neural network

Abstract

A method for predicting prison term based on multi-task artificial neural network includes such steps as analyzing and mining the data of judgment document, predicting the term of imprisonment of newly obtained description of crime fact and basic information of suspect, predicting the term of imprisonment of newly obtained description of crime fact and basic information of suspect, predicting theterm of imprisonment of newly obtained description of crime fact, predicting the term of imprisonment of newly acquired description of crime, predicting the term of imprisonment of newly obtained description of crime and basic information of suspect, predicting the term of imprisonment of newly obtained description of crime, and predicting the term of imprisonment of newly obtained suspect. Guidedby the attributes of legal clauses cited in judgment documents, this method constructs a multi-task neural network model with mutual support effect by making full use of the multi-dimensional data injudgment documents, and trains the pre-processed judgment documents data to obtain a predictive method with high precision and strong practicability. This method takes 21 legal articles such as accusation, degree of injury and amount of money involved as auxiliary tasks, and classifies life sentence and death sentence separately, so as to achieve accurate prediction of sentence. Compared with thesingle-task neural network model based on such attributes, the prediction accuracy rate of the method proposed by the invention is higher, indicating that the method proposed by the invention is effective and practical.

Description

technical field [0001] The invention relates to a method for predicting a sentence based on a multi-task artificial neural network, which belongs to the technical field of natural language processing. Background technique [0002] The sentence prediction problem is one of the important basic problems in the information mining and analysis of judgment documents. Its goal is to predict the sentence that will be imposed on the basis of the crime facts based on the law and other relevant information based on the description of the crime facts. It can be used for subsequent automatic trials and legal intelligent consultation. In recent years, the development and application of natural language processing technology based on neural network has greatly promoted the development of referee document information processing and mining. The traditional sentence prediction method based on artificial neural network is based on the description of criminal facts and directly predicts the se...

AI Technical Summary

Problems solved by technology

[0004] Although the sentence prediction method based on the artificial neural network has realized the intelligent mining and utilization of judgment document information to a certain extent, the traditional sentence prediction method based on the artificial neural network directly predicts the sentence according to the description of the crime facts, and has not been fully utilized. The large amount of information contained in the judgment documents ignores the correlation between the sentence and various information in other dimensions. The sentence prediction method based on the single-task artificial neural network only takes the facts of the crime as the input and the sentence as the output, ignoring the fact in the judgment documents. The correlation between useful information in various dimensions, such as charges, basic information of suspects, and attribute information described by criminal facts, leads to problems such as poor convergence of model training and large deviations in actual prediction results, making it difficult to meet practical application requirements

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