@inproceedings{34c686cd4cb549439452b604d25dfd0b,
title = "Automatic Taxonomy Generation: A Use-Case in the Legal Domain",
abstract = "A key challenge in the legal domain is the adaptation and representation of the legal knowledge expressed through texts, in order for legal practitioners and researchers to access this information more easily and faster to help with compliance related issues. One way to approach this goal is in the form of a taxonomy of legal concepts. While this task usually requires a manual construction of terms and their relations by domain experts, this paper describes a methodology to automatically generate a taxonomy of legal noun concepts. We apply and compare two approaches on a corpus consisting of statutory instruments for UK, Wales, Scotland and Northern Ireland laws.",
keywords = "Hierarchical embedding clustering, Legal domain, Taxonomy generation, Topic hierarchy",
author = "C{\'e}cile Robin and James O{\textquoteright}Neill and Paul Buitelaar",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 8th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2017 ; Conference date: 17-11-2017 Through 19-11-2017",
year = "2020",
doi = "10.1007/978-3-030-66527-2\_23",
language = "English",
isbn = "9783030665265",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "318--328",
editor = "Zygmunt Vetulani and Patrick Paroubek and Marek Kubis",
booktitle = "Human Language Technology. Challenges for Computer Science and Linguistics - 8th Language and Technology Conference, LTC 2017, Revised Selected Papers",
}