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Headnote prediction using machine learning
Joint Authors
Mahar, Sarmad
Zafar, Sahar
Nishat, Kamran
Source
The International Arab Journal of Information Technology
Issue
Vol. 18, Issue 5 (30 Sep. 2021), pp.678-685, 8 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2021-09-30
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
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 trigram 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.
American Psychological Association (APA)
Mahar, Sarmad& Zafar, Sahar& Nishat, Kamran. 2021. Headnote prediction using machine learning. The International Arab Journal of Information Technology،Vol. 18, no. 5, pp.678-685.
https://search.emarefa.net/detail/BIM-1431112
Modern Language Association (MLA)
Mahar, Sarmad…[et al.]. Headnote prediction using machine learning. The International Arab Journal of Information Technology Vol. 18, no. 5 (Sep. 2021), pp.678-685.
https://search.emarefa.net/detail/BIM-1431112
American Medical Association (AMA)
Mahar, Sarmad& Zafar, Sahar& Nishat, Kamran. Headnote prediction using machine learning. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 5, pp.678-685.
https://search.emarefa.net/detail/BIM-1431112
Data Type
Journal Articles
Language
English
Notes
Text in English ; abstracts in .
Record ID
BIM-1431112