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

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.