A Text Similarity Approach for Automated Transposition Detection of European Union Directives

Rohan Nanda; Luigi Di Caro; Guido Boella

doi:10.3233/978-1-61499-726-9-143

A Text Similarity Approach for Automated Transposition Detection of European Union Directives

Rohan Nanda^*, Luigi Di Caro, Guido Boella

^*Corresponding author for this work

Research output: Contribution to conference › Paper › Academic

Abstract

This paper investigates the application of text similarity techniques to automatically detect the transposition of European Union (EU) directives into the national law. Currently, the European Commission (EC) resorts to time-consuming and expensive manual methods like conformity checking studies and legal analysis for identifying national transposition measures. We utilize both lexical and semantic similarity techniques and supplement them with knowledge from EuroVoc to identify transpositions. We then evaluate our approach by comparing the results with the correlation tables (gold standard). Our results indicate that both similarity techniques proved to be effective in detecting transpositions. Such systems could be used to identify the transposed provisions by both EC and legal professionals.

Original language	English
Pages	143-148
DOIs	https://doi.org/10.3233/978-1-61499-726-9-143
Publication status	Published - 2016
Externally published	Yes

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10.3233/978-1-61499-726-9-143

Cite this

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title = "A Text Similarity Approach for Automated Transposition Detection of European Union Directives",

abstract = "This paper investigates the application of text similarity techniques to automatically detect the transposition of European Union (EU) directives into the national law. Currently, the European Commission (EC) resorts to time-consuming and expensive manual methods like conformity checking studies and legal analysis for identifying national transposition measures. We utilize both lexical and semantic similarity techniques and supplement them with knowledge from EuroVoc to identify transpositions. We then evaluate our approach by comparing the results with the correlation tables (gold standard). Our results indicate that both similarity techniques proved to be effective in detecting transpositions. Such systems could be used to identify the transposed provisions by both EC and legal professionals.",

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PY - 2016

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AB - This paper investigates the application of text similarity techniques to automatically detect the transposition of European Union (EU) directives into the national law. Currently, the European Commission (EC) resorts to time-consuming and expensive manual methods like conformity checking studies and legal analysis for identifying national transposition measures. We utilize both lexical and semantic similarity techniques and supplement them with knowledge from EuroVoc to identify transpositions. We then evaluate our approach by comparing the results with the correlation tables (gold standard). Our results indicate that both similarity techniques proved to be effective in detecting transpositions. Such systems could be used to identify the transposed provisions by both EC and legal professionals.

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