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Change-aware legal document retrieval model

Published:26 October 2010Publication History

ABSTRACT

Legal documents play a basic role in discharging the law to the public, besides constituting learning material for students, researchers and legal practitioners. Legal documents contain text rich contents that can be structured and marked with description languages such as XML. This basic feature can be exploited by XML based retrieval models to return legal document parts that are more relevant as compared to the query results by the traditional Information Retrieval (IR) systems.

Under different paradigms, legal documents are subject to change, as the laws they carry undergo modifications or amendments. The dynamicity of the law is manifested by the change in the legal documents, which may be caused for example by the socio-economic changes of the society that it is serving. This change in turn will have a sever consequence on the retrieval quality of the legal document retrieval systems. However, none of the legal document retrieval systems considered the dynamic feature of legal documents over time in their search and retrieval systems.

In this work we propose a generic model for a change-aware legal document retrieval system using XML based IR approaches. Based on the model, we have designed the necessary algorithms to implement the system and developed a prototype system that demonstrates the validity of our proposed model. The experiments we conducted show that the system developed based on our model have a significant precision improvement.

References

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  1. Change-aware legal document retrieval model

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    • Published in

      cover image ACM Other conferences
      MEDES '10: Proceedings of the International Conference on Management of Emergent Digital EcoSystems
      October 2010
      302 pages
      ISBN:9781450300476
      DOI:10.1145/1936254

      Copyright © 2010 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 26 October 2010

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      MEDES '10 Paper Acceptance Rate26of93submissions,28%Overall Acceptance Rate267of682submissions,39%

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