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Intelligent Systems Technologies and Applications pp 355–368Cite as

Categorisation of Supreme Court Cases Using Multiple Horizontal Thesauri

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 385))

Abstract

Text classification is a branch of Artificial Intelligence which deals with the assignment of textual documents to a controlled group of classes. The aim of this paper is to assess the use of a controlled vocabulary in the categorisation of legal texts. Controlled vocabularies such as the Medical Subject Headings, Compendex and AGROVOC have been proved to be very useful in the fields of biomedical research, engineering and agriculture, respectively. In this work, a number of lexicons are created for some pre-defined areas of law through an automated approach. The lexicons are then used to categorise cases from the Supreme Court into eight distinct areas of law. We then compared the performance of these lexicons with each other. We found that lexicons which have a mixture of single words and short phrases performs slightly better than those consisting simply of single words. Weights were also assigned to the terms and this had a significant positive impact on the classification accuracy. The number of words in each thesaurus was kept constant. A hierarchical classification was also attempted whereby cases were first classified into either a civil case or a criminal case. Civil cases were then further classified into company, labour, contract and land cases while criminal cases were classified into drugs, homicide, road traffic offences and other criminal offences. Our best model achieves a global accuracy of 78.9 %. Thus, we have demonstrated that it is possible to get good classification accuracies with legal cases through the use of automatically generated thesauri. This outcome of this research can become an integral part of the eJudiciary project that has already been initiated by the government. In line with the vision of the Judiciary, we are hereby in the process of creating an intelligent legal information system which will benefit all legal actors and will have a definite positive impact on the legal landscape of the Republic of Mauritius. Lawyers, attorneys and their assistants would spend less time on legal research and hence they would have more time to prepare their arguments for their case. We are optimistic in believing that this will make the whole business of providing justice more effective and more efficient through the reduction in postponement of cases and a reduction in the average disposal time of cases.

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Author information

Authors and Affiliations

  1. Department of Ocean Engineering & ICT, Faculty of Ocean Studies, University of Mauritius, Moka, Mauritius

    Sameerchand Pudaruth

  2. Electrical and Electronic Engineering Department, Faculty of Engineering, University of Mauritius, Moka, Mauritius

    K. M. Sunjiv Soydaudah

  3. Department of Law, Faculty of Law and Management, University of Mauritius, Moka, Mauritius

    Rajendra Parsad Gunputh

Authors
  1. Sameerchand Pudaruth
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  2. K. M. Sunjiv Soydaudah
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  3. Rajendra Parsad Gunputh
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Correspondence to Sameerchand Pudaruth .

Editor information

Editors and Affiliations

  1. Dipartimento di Ingegneria dell’ Informazione (DINFO) , Universita degli Studi di Firenze, Firenze, Italy

    Stefano Berretti

  2. School of CS/IT, Indian Institute of Information Tech. and Management – Kerala (IIITM-K), Trivandrum, India

    Sabu M. Thampi

  3. Electrical and Computer Engineering, The University of Iowa College of Engineering, Iowa, Iowa, USA

    Soura Dasgupta

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Pudaruth, S., Soydaudah, K.M.S., Gunputh, R.P. (2016). Categorisation of Supreme Court Cases Using Multiple Horizontal Thesauri. In: Berretti, S., Thampi, S., Dasgupta, S. (eds) Intelligent Systems Technologies and Applications. Advances in Intelligent Systems and Computing, vol 385. Springer, Cham. https://doi.org/10.1007/978-3-319-23258-4_31

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  • DOI: https://doi.org/10.1007/978-3-319-23258-4_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23257-7

  • Online ISBN: 978-3-319-23258-4

  • eBook Packages: EngineeringEngineering (R0)

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