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Fuzzy AHP approach for legal judgement summarization

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  • Neha Bansal
  • Arun Sharma
  • R. K. Singh

Abstract

Legal documents are generally big and complex documents because of specific vocabulary, semantics and structure. One of the major challenges in legal processing systems is to generate summary of legal judgements. Till date, in most of the legal systems, the summary of judgements is produced manually by legal experts which are then used by Lawyers, Judges and other legal professionals. The manual process of summarization is very inefficient and time-consuming. Automatic text summarization (ATS) is the process of reducing the content of a textual document, while retaining the core description of text through the use of appropriate tool. The present work proposes a novel Fuzzy Analytical Hierarchical process (FAHP) based feature weighting scheme which helps in producing an efficient and effective summary of legal judgement. Model is applied on a number of legal judgements taken from Indian IT Act. Validation of the model is done using ROUGE (Recall-Oriented Understudy for Gisting Evaluation) tool with recall, precision, and f-measure as performance measures. The generated summaries are further assessed by legal experts and are found to be more promising than the summaries generated by traditional approaches.

Suggested Citation

  • Neha Bansal & Arun Sharma & R. K. Singh, 2019. "Fuzzy AHP approach for legal judgement summarization," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(3), pages 323-340, July.
    • Handle: RePEc:taf:tjmaxx:v:6:y:2019:i:3:p:323-340
    DOI: 10.1080/23270012.2019.1655672
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    Cited by:

    1. Tao Shu & Zhiyi Wang & Huading Jia & Wenjin Zhao & Jixian Zhou & Tao Peng, 2022. "Consumers’ Opinions towards Public Health Effects of Online Games: An Empirical Study Based on Social Media Comments in China," IJERPH, MDPI, vol. 19(19), pages 1-19, October.
    2. Arpan Kumar Kar & P. S. Varsha & Shivakami Rajan, 2023. "Unravelling the Impact of Generative Artificial Intelligence (GAI) in Industrial Applications: A Review of Scientific and Grey Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 659-689, December.

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