scholarly journals Text Classification in Law Area: a Systematic Review

2021 ◽  
Author(s):  
V. S. Martins ◽  
C. D. Silva

Automatic Text Classification represents a great improvement in law area workflow, mainly in the migration of physical to electronic lawsuits. A systematic review of studies on text classification in law area from January 2017 up to February 2020 was conducted. The search strategy identified 20 studies, that were analyzed and compared. The review investigates from research questions: what are the state-of-art language models, its application of text classification in English and Brazilian Portuguese datasets from legal area, if there are available language models trained on Brazilian Portuguese, and datasets in Brazilian law area. It concludes that there are applications of automatic text classification in Brazil, although there is a gap on the use of language models when compared with English language dataset studies, also the importance of language model in domain pre-training to improve results, as well as there are two studies making available Brazilian Portuguese language models, and one introducing a dataset in Brazilian law area.

SCITECH Nepal ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. 64-69
Author(s):  
Dinesh Dangol ◽  
Rupesh Dahi Shrestha ◽  
Arun Timalsina

With an increasing trend of publishing news online on website, automatic text processing becomes more and more important. Automatic text classification has been a focus of many researchers in different languages for decades. There is a huge amount of research repository on features of English language and their uses on automated text processing. This research implements Nepali language key features for automatic text classification of Nepali news. In particular, the study on impact of Nepali language based features, which are extremely different than English language is more challenging because of the higher level of complexity to be resolved. The research experiment using vector space model, n-gram model and key feature based processing specific to Nepali language shows promising result compared to bag-of-words model for the task of automated Nepali news classification.


10.2196/16929 ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. e16929
Author(s):  
Michelle Helena Van Velthoven ◽  
Madison Milne-Ives ◽  
Caroline de Cock ◽  
Mary Mooney ◽  
Edward Meinert

Background The decline in the uptake of routine childhood vaccinations has resulted in outbreaks of vaccine-preventable diseases. Vaccination apps can be used as a tool to promote immunization through the provision of reminders, dissemination of information, peer support, and feedback. Objective The aim of this review is to systematically review the evidence on the use of apps to support childhood vaccination uptake, information storage, and record sharing. Methods We will identify relevant papers by searching the following electronic databases: PubMed, Embase by Ovid, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), ClinicalTrials.gov, and Education Resources Information Center (ERIC). We will review the reference lists of those studies that we include to identify relevant additional papers not initially identified using our search strategy. In addition to the use of electronic databases, we will search for grey literature on the topic. The search strategy will include only terms relating to or describing the intervention, which is app use. As almost all titles and abstracts are in English, 100% of these will be reviewed, but retrieval will be confined to papers written in the English language. We will record the search outcome on a specifically designed record sheet. Two reviewers will select observational and intervention studies, appraise the quality of the studies, and extract the relevant data. All studies will involve the use of apps relating to child vaccinations. The primary outcome is the uptake of vaccinations. Secondary outcomes are as follows: (1) use of app for sharing of information and providing vaccination reminders and (2) use of app for storage of vaccination information; knowledge and decision making by parents regarding vaccination (ie, risks and benefits of vaccination); costs and cost-effectiveness of vaccination apps; use of the app and measures of usability (eg, usefulness, acceptability, and experiences of different users: parents and health care professionals); use of technical standards for development of the app; and adverse events (eg, data leaks and misinformation). We will exclude studies that do not study an app. We anticipate a limited scope for meta-analysis and will provide a narrative overview of findings and tabular summaries of extracted data. Results This project was funded by the Sir David Cooksey Fellowship in Healthcare Translation at the University of Oxford, Oxford, United Kingdom. We will submit the full systematic review for publication in the Journal of Medical Internet Research. Conclusions This review will follow, where possible, the Cochrane Collaboration and the Centre for Review and Dissemination methodologies for conducting systematic reviews. We will report our findings based on guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The review results will be used to inform the development of a vaccination app. International Registered Report Identifier (IRRID) PRR1-10.2196/16929


2020 ◽  
Vol 54 (3) ◽  
pp. 113-123
Author(s):  
V. S. Egorov ◽  
E. S. Kozlova ◽  
K. E. Lomotin ◽  
O. V. Fedorets ◽  
A. V. Filimonov ◽  
...  

2008 ◽  
Vol E91-D (4) ◽  
pp. 1101-1109 ◽  
Author(s):  
L. S.P. BUSAGALA ◽  
W. OHYAMA ◽  
T. WAKABAYASHI ◽  
F. KIMURA

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