scholarly journals Identification of Judicial Outcomes in Judgments: A Generalized Gini-PLS Approach

Stats ◽  
2020 ◽  
Vol 3 (4) ◽  
pp. 427-443
Author(s):  
Gildas Tagny-Ngompé ◽  
Stéphane Mussard ◽  
Guillaume Zambrano ◽  
Sébastien Harispe ◽  
Jacky Montmain
Keyword(s):  
Law Enforcement ◽  
Success Rate ◽  
Text Classification ◽  
Binary Classification ◽  
Classification Algorithms ◽  
Classification Models ◽  
Target Variable ◽  
Technical Aspects ◽  
Legal Documents ◽  
Judicial Outcomes

This paper presents and compares several text classification models that can be used to extract the outcome of a judgment from justice decisions, i.e., legal documents summarizing the different rulings made by a judge. Such models can be used to gather important statistics about cases, e.g., success rate based on specific characteristics of cases’ parties or jurisdiction, and are therefore important for the development of Judicial prediction not to mention the study of Law enforcement in general. We propose in particular the generalized Gini-PLS which better considers the information in the distribution tails while attenuating, as in the simple Gini-PLS, the influence exerted by outliers. Modeling the studied task as a supervised binary classification, we also introduce the LOGIT-Gini-PLS suited to the explanation of a binary target variable. In addition, various technical aspects regarding the evaluated text classification approaches which consists of combinations of representations of judgments and classification algorithms are studied using an annotated corpora of French justice decisions.

scholarly journals Machine-Learning-Based Radiomics MRI Model for Survival Prediction of Recurrent Glioblastomas Treated with Bevacizumab

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1263
Author(s):  
Samy Ammari ◽  
Raoul Sallé de Chou ◽  
Tarek Assi ◽  
Mehdi Touat ◽  
Emilie Chouzenoux ◽  
...  
Keyword(s):  
Machine Learning ◽  
Therapeutic Option ◽  
Binary Classification ◽  
Progression Free Survival ◽  
Recurrent Glioblastoma ◽  
Machine Learning Algorithms ◽  
Survival Prediction ◽  
Classification Models ◽  
Angiogenic Therapy ◽  
Recurrent Gbm

Anti-angiogenic therapy with bevacizumab is a widely used therapeutic option for recurrent glioblastoma (GBM). Nevertheless, the therapeutic response remains highly heterogeneous among GBM patients with discordant outcomes. Recent data have shown that radiomics, an advanced recent imaging analysis method, can help to predict both prognosis and therapy in a multitude of solid tumours. The objective of this study was to identify novel biomarkers, extracted from MRI and clinical data, which could predict overall survival (OS) and progression-free survival (PFS) in GBM patients treated with bevacizumab using machine-learning algorithms. In a cohort of 194 recurrent GBM patients (age range 18–80), radiomics data from pre-treatment T2 FLAIR and gadolinium-injected MRI images along with clinical features were analysed. Binary classification models for OS at 9, 12, and 15 months were evaluated. Our classification models successfully stratified the OS. The AUCs were equal to 0.78, 0.85, and 0.76 on the test sets (0.79, 0.82, and 0.87 on the training sets) for the 9-, 12-, and 15-month endpoints, respectively. Regressions yielded a C-index of 0.64 (0.74) for OS and 0.57 (0.69) for PFS. These results suggest that radiomics could assist in the elaboration of a predictive model for treatment selection in recurrent GBM patients.

scholarly journals The Accuracy of the Tick Rule in the Bitcoin Market

SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110145
Author(s):  
Donglian Ma ◽  
Pengxiang Zhai
Keyword(s):  
Success Rate ◽  
Sufficient Accuracy ◽  
Classification Algorithms ◽  
Market Data ◽  
Long Period ◽  
Trade Classification

The tick rule is one of the most popular trade classification algorithms used when an order initiator in market data is not signed. Using 11.9 million trades of Bitcoin/USD on Bitstamp, this article tests the accuracy of the tick rule in the Bitcoin market. Evidence indicates that the overall success rate of the tick rule is 76.87%. It is also shown that the tick rule is inclined to fail in discerning trade intentions when there is a long period of time between trades. Furthermore, order imbalances computed using the tick rule lack sufficient accuracy in the Bitcoin market.

Headnote Prediction Using Machine Learning

2021 ◽  
Vol 18 (5) ◽  
Author(s):  
Sarmad Mahar ◽  
Sahar Zafar ◽  
Kamran Nishat
Keyword(s):  
Machine Learning ◽  
Feature Extraction ◽  
Active Learning ◽  
Text Classification ◽  
Extraction Methods ◽  
Text Summarization ◽  
Training Data ◽  
Second Step ◽  
Support Vector ◽  
Classification Algorithms

Headnotes are the precise explanation and summary of legal points in an issued judgment. Law journals hire experienced lawyers to write these headnotes. These headnotes help the reader quickly determine the issue discussed in the case. Headnotes comprise two parts. The first part comprises the topic discussed in the judgment, and the second part contains a summary of that judgment. In this thesis, we design, develop and evaluate headnote prediction using machine learning, without involving human involvement. We divided this task into a two steps process. In the first step, we predict law points used in the judgment by using text classification algorithms. The second step generates a summary of the judgment using text summarization techniques. To achieve this task, we created a Databank by extracting data from different law sources in Pakistan. We labelled training data generated based on Pakistan law websites. We tested different feature extraction methods on judiciary data to improve our system. Using these feature extraction methods, we developed a dictionary of terminology for ease of reference and utility. Our approach achieves 65% accuracy by using Linear Support Vector Classification with tri-gram and without stemmer. Using active learning our system can continuously improve the accuracy with the increased labelled examples provided by the users of the system.

scholarly journals Analysis of Text Classification Algorithms: A Review

2019 ◽  
Vol Volume-3 (Issue-2) ◽  
pp. 579-581
Author(s):  
Nida Zafar Khan ◽  
Prof. S. R. Yadav ◽  
Keyword(s):  
Text Classification ◽  
Classification Algorithms

scholarly journals The Development of E-Learning Tools Used for Teaching English for Law Enforcement

2021 ◽  
Vol 13 (1) ◽  
pp. 181-200
Author(s):  
Judit Borszéki
Keyword(s):  
Law Enforcement ◽  
Police Officers ◽  
English Language ◽  
Learning Tools ◽  
Teaching English ◽  
Legal Documents ◽  
Real Presence ◽  
Language Courses ◽  
E Learning ◽  
Training Courses

International (operational and training) activities carried out by law enforcement officers have been accompanied by the growing realisation of the fact that it is essential for those involved in them to communicate efficiently, in one common language, basically English. However, even in the last few years, the gaps between the foreign language skills of the law enforcement professionals and the need for further foreign (mainly English) language training courses have been underlined several times in international professional and legal documents. Also, the fact that specific-purpose English language courses continue to be important content elements of the curricula both of national law enforcement training institutions and the two largest EU agencies involved in the training of police officers, as well as border and coast guards (CEPOL and Frontex), proves that this problem still exists. Using the qualitative research and providing an overview and evaluation of the most significant e-learning trends and tools used in teaching English for Law Enforcement by CEPOL and Frontex in the last decade, the paper discusses the progress made in this field in terms of both quality and methodology. It presents technical limitations of certain e-learning tools and points to the course developers’ ensuing realisation that the virtual or real presence of the teacher is indispensable in language courses.

scholarly journals Administrative Law Aspects of Bringing Employees of Prosecution Authorities to Disciplinary Liability

2020 ◽  
Vol 12 ◽  
pp. 59-61
Author(s):  
Vladilen V. Strelnikov ◽  
Keyword(s):  
Law Enforcement ◽  
Public Service ◽  
Administrative Law ◽  
Practical Implementation ◽  
Scientific Article ◽  
Legal Analysis ◽  
Law Enforcement Agencies ◽  
Legal Norms ◽  
The Public ◽  
Legal Documents

The scientific article analyses issues related to the practical implementation of legal norms governing the procedure for disciplinary liability of prosecutors. A theoretical analysis of the interpretations of disciplinary responsibility in the public service formulated by leading legal scholars was carried out. A comparative legal analysis has been carried out of the regulations governing the procedure for the imposition of disciplinary penalties in State bodies, including law enforcement agencies and the legal documents governing these issues in the prosecutor’s office.

scholarly journals Criminal Liability for Provoking Bribery

2021 ◽  
Vol 39 (69) ◽  
pp. 492-512
Author(s):  
Oksana Stepanenko ◽  
Andriy Stepanenko ◽  
Maryna Shepotko
Keyword(s):  
Law Enforcement ◽  
Public Relations ◽  
Analytical Method ◽  
Criminal Liability ◽  
Law Enforcement Agencies ◽  
Distinctive Features ◽  
Historical Method ◽  
Legal Documents ◽  
New Challenges ◽  
Quantitative Indicators

In modern conditions of development of public relations complication of activity of law enforcement agencies is observed. This is due to new challenges in the law enforcement system, including the fight against high levels of the organization and the criminal professionalism of corrupt individuals. Because of this, it is challenging for operational units to identify specific facts of illegal actions with the help of operational and investigative measures. At the same time, the fight against crime by establishing high quantitative indicators of disclosure remains one of the principles of law enforcement in Ukraine, including sometimes deviating from those means established by law. Therefore, the problem of provoking bribery is relevant for scholars of the legislator and law enforcement. The object of the study is criminal liability for provoking bribery. The research methodology consists of such methods as the dialectical method, analytical method, historical method, method of analysis of legal documents, articles, and monographs, method of generalization, comparison, synthesis, and modeling method. The authors identified the features of such liability to clarify the problematic issues of qualification of provoking bribery, and to distinguish the distinctive features of prosecution from other types of crimes.

scholarly journals Definition Extraction from Generic and Mathematical Domains with Deep Ensemble Learning

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2502
Author(s):  
Natalia Vanetik ◽  
Marina Litvak
Keyword(s):  
Semantic Information ◽  
State Of The Art ◽  
Binary Classification ◽  
Ensemble Model ◽  
Classification Models ◽  
New Materials ◽  
Educational Materials ◽  
Efficient Learning ◽  
Mathematical Definitions

Definitions are extremely important for efficient learning of new materials. In particular, mathematical definitions are necessary for understanding mathematics-related areas. Automated extraction of definitions could be very useful for automated indexing educational materials, building taxonomies of relevant concepts, and more. For definitions that are contained within a single sentence, this problem can be viewed as a binary classification of sentences into definitions and non-definitions. In this paper, we focus on automatic detection of one-sentence definitions in mathematical and general texts. We experiment with different classification models arranged in an ensemble and applied to a sentence representation containing syntactic and semantic information, to classify sentences. Our ensemble model is applied to the data adjusted with oversampling. Our experiments demonstrate the superiority of our approach over state-of-the-art methods in both general and mathematical domains.

Biometric methods and their application in the Police investigation work

2021 ◽  
pp. 41-52
Author(s):  
Edyta Kot ◽  
◽  
Anna Jurga ◽  
Ewa Kartasińska ◽  
Ewa Lewansowska ◽  
...  
Keyword(s):  
Law Enforcement ◽  
Daily Basis ◽  
Biometric Data ◽  
Technical Aspects ◽  
Detection Techniques ◽  
The Past ◽  
Police Investigation ◽  
Practical Guidance ◽  
Near Future ◽  
Data Collection Procedure

Biometrics is one of the basic detection techniques used in law enforcement activities on a daily basis. Like other techniques, it is constantly changing. This article aims to provide an overview of what was in the past, what is now, and what will be in the near future. It presents the selected methods of collecting some of the data, as well as the systems used to process them. In addition, practical guidance is provided on how individual biometric data should be collected and, for specific cases, it explains why the data collection procedure is carried out in one way and not another, and what it means for its subsequent processing. As problems sometimes arise during recovery of the material they have been presented together with an overview of the reasons for that. In addition to information on the technical aspects, the article also includes references to legal acts regulating issues related to biometrics.

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