Search method for ordinances and rules in Japanese local governments based on distributed representation

Abstract

This paper proposes a new search method that supports legislative duties in Japanese local governments where both expert and non-experts draft local ordinances. Since such legislation requires comparison with the ordinances of other local governments, our purpose is to introduce a neural model and show how it effectively performs similarity search tasks for ordinances. Our experimental results show that our method outperforms the previous scheme for similarity search with a F-measure of 0.977. An additional experiment shows that our method is useful for analyzing the legislation of local governments.