A text mining approach to assist the general public in the retrieval of legal documents

Chen, Yen-Liang; Liu, Yi-Hung; Ho, Wu-Liang

doi:10.1002/asi.22767

Cited by 37 publications

(30 citation statements)

References 27 publications

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“…The work of charge prediction is also related to the legal assistant systems. In this field, answering legal questions and searching relevant cases have been extensively studied [13], [42], [43]. Some attempts consider charge prediction as a part of the automatic judgment prediction [44]- [46].…”

Section: Introductionmentioning

confidence: 99%

A Neural-Network-Based Model of Charge Prediction via the Judicial Interpretation of Crimes

Kang

Wang

et al. 2020

IEEE Access

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The neural-network-based charge prediction, which is to predict the defendants' charges from the criminal case documents via neural network, has been a development-potential affair in artificial intelligence (AI) based legal assistant system and made some achievements. Neural network is playing important role to capture deep information in current work. However, charge prediction suffers from serious data imbalance in real-world situation. Only high-frequency charges are easy to be predicted whereas plenty of low-frequency ones are hard to be hold. Furthermore, the presence of confusing charges makes prediction worse. Here, we propose a novel model of charge prediction via the judicial interpretation of crimes (CPJIC) to provide more accurate charge prediction. The concept of crime interpretation is introduced into CPJIC, which alleviates the problems resulted from data imbalance and confusing charges. With the technique of embedding, both fact description and crime interpretation are embedded into a low-dimensional vector space as well as a neural network, delivering implemented computable charge prediction. The experimental results demonstrate that CPJIC can identify the low-frequency and confusing charges better than previous work.

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Section: Introductionmentioning

confidence: 99%

A Neural-Network-Based Model of Charge Prediction via the Judicial Interpretation of Crimes

Kang

Wang

et al. 2020

IEEE Access

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“…M Lei based on Machine Learning algorithms to implement automatic classification of Chinese Judgment Documents [3]. YL Chen designed a textmining-based method that allows the general public to use everyday vocabulary to search for and retrieve criminal judgments [4].Similar researches mostly make statistics on the contents of referees' documents through statistical knowledge and find out some superficial rules in the documents. The work of this paper is to predict how many years a criminal suspect can sentence given by continuously studying the features of cases in the arbitration instruments, which can be used as a reference for lawyers and clients.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Criminal Case Judgment Documents Based on Deep Learning

Han¹,

Li²,

Yang³

et al. 2018

Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)

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In recent years, along with the improvement of population quality and the advancement of the rule of law society, the market for legal services in the middle and low-end markets has continued to expand, and legal advice has become widespread in daily life. In the process of legal services, the legal provisions play an important role in the lawyer's decisionmaking. Meanwhile, the historical cases can help the lawyers and the parties to draw lessons from similar cases. However, with the increasing number of judicial documents, it is becoming increasingly difficult to summarize and learn from history. Therefore, this paper proposes a sentencing interval prediction model of criminal cases based on convolutional neural network, and through the method of multi-core convolution, greatly enhances the generalization ability and prediction performance of the model. The experimental analysis of real criminal case verdict verifies that the model is more effective than other classification prediction algorithms.

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“…Text mining has been widely applied in various disciplines. Only a few studies, however, have examined text mining in the legal field [2–8]. Furthermore, several online forums for legal systems are available that provide news, insights and professional discussions (Above the Law, 3 Legal Informatics Blog, 4 and The Crime Report 5 ).…”

Section: Introductionmentioning

confidence: 99%

A two-phase sentiment analysis approach for judgement prediction

Liu

Chen

2017

Journal of Information Science

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Factual scenario analysis of a judgement is critical to judges during sentencing. With the increasing number of legal cases, professionals typically endure heavy workloads on a daily basis. Although a few previous studies have applied information technology to legal cases, according to our research, no prior studies have predicted a pending judgement using legal documents. In this article, we introduce an innovative solution to predict relevant rulings. The proposed approach employs text mining methods to extract features from precedents and applies a text classifier to automatically classify judgements according to sentiment analysis. This approach can assist legal experts or litigants in predicting possible judgements. Experimental results from a judgement data set reveal that our approach is a satisfactory method for judgement classification.

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A text mining approach to assist the general public in the retrieval of legal documents

Cited by 37 publications

References 27 publications

A Neural-Network-Based Model of Charge Prediction via the Judicial Interpretation of Crimes

A Neural-Network-Based Model of Charge Prediction via the Judicial Interpretation of Crimes

Analysis of Criminal Case Judgment Documents Based on Deep Learning

A two-phase sentiment analysis approach for judgement prediction

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