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Application of Network Analysis for Finding Relatedness among Legal Documents by Using Case Citation Data

Nidha Khanam*, Rupali Sunil Wagh**

* PG Scholar, Department of Computer Science Engineering, Christ University, Bangalore, Karnataka, India.

** Associate Professor, Department of Computer Science Engineering, Christ University, Bangalore, Karnataka, India.

Periodicity:September - November'2017
DOI : https://doi.org/10.26634/jit.6.4.13847

Abstract

Information Retrieval (IR) is an activity of searching and extracting information from web resources based on the information need of user. There are various domains like legal domain where information being searched is stored in large databases and is available as documents written in natural languages. Due to the huge amount of information being available as text documents, there is a paradigm shift towards knowledge based information retrieval. Knowledge management requirements of legal domain are very challenging due to the complex structure of legal documents like acts, judgments, petitions, etc. Citations across these documents thus can be considered as very important component in legal processes. Citation analysis in legal domain is used to examine the patterns to find the relationship between the legal documents. Citations can be represented as network of legal documents where every document represents a legal concept. In this study, similarities between legal documents are analyzed and visualized using Network Analysis. Unlike other techniques where similarity is defined between two objects directly, network analysis allows to analyze relatedness with the help of betweenness and paths. Citations in the judgements of Indian courts are used to build the network structure which is then evaluated using network metrics.

Keywords

Information Retrieval, Legal Documents, Citation Analysis, Similarity Search, Citation Network

How to Cite this Article?

Khanam, N., and Wagn, R. (2017). Application of Network Analysis for Finding Relatedness among Legal Documents by Using Case Citation Data. i-manager’s Journal on Information Technology, 6(4), 23-29. https://doi.org/10.26634/jit.6.4.13847

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