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  Simplify Your Law: Using Information Theory to Deduplicate Legal Documents

Coupette, C., Singh, J., & Spamann, H. (2021). Simplify Your Law: Using Information Theory to Deduplicate Legal Documents. In IEEE (Ed.), 2021 International Conference on Data Mining Workshops (ICDMW) (pp. 631-638).

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Genre: Conference Paper

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 Creators:
Coupette, Corinna1, Author           
Singh, Jyotsna2, Author
Spamann, Holger2, Author
Affiliations:
1Business and Tax Law, MPI for Tax Law and Public Finance, Max Planck Society, ou_830551              
2External Organizations, ou_persistent22              

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Free keywords: law, information theory, minimum description length, text mining, sequence mining
 Abstract: Textual redundancy is one of the main challenges to ensuring that legal texts remain comprehensible and maintainable. Drawing inspiration from the refactoring literature in software engineering, which has developed methods to expose and eliminate duplicated code, we introduce the duplicated phrase detection problem for legal texts and propose the Dupex algorithm to solve it. Leveraging the Minimum Description Length principle from information theory, Dupex identifies a set of duplicated phrases, called patterns, that together best compress a given input text. Through an extensive set of experiments on the Titles of the United States Code, we confirm that our algorithm works well in practice: Dupex will help you simplify your law.

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Language(s): eng - English
 Dates: 2021
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1109/ICDMW53433.2021.00083
 Degree: -

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Title: 2021 International Conference on Data Mining Workshops (ICDMW)
Place of Event: Auckland
Start-/End Date: 2021-12-07 - 2021-12-10

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Title: 2021 International Conference on Data Mining Workshops (ICDMW)
Source Genre: Proceedings
 Creator(s):
IEEE, Editor              
Affiliations:
-
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 631 - 638 Identifier: ISBN: 978-1-6654-2428-8