An analysis of topic modelling for legislative texts
| dc.contributor.author | O'Neill, James | |
| dc.contributor.author | Robin, Cecile | |
| dc.contributor.author | O'Brien, Leona | |
| dc.contributor.author | Buitelaar, Paul | |
| dc.date.accessioned | 2018-09-13T11:46:39Z | |
| dc.date.available | 2018-09-13T11:46:39Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | The uprise of legislative documents within the past decade has risen dramatically, making it difficult for law practitioners to attend to legislation such as Statutory Instrument orders and Acts. This work focuses on the use of topic models for summarizing and visualizing British legislation, with a view toward easier browsing and identification of salient legal topics and their respective set of topic specific terms. We provide an initial qualitative evaluation from a legal expert on how the models have performed by ranking them for each jurisdiction according to topic coherency and relevance. | en |
| dc.description.status | Peer reviewed | en |
| dc.description.version | Accepted Version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | O'Neill, J., Robin, C., O'Brien, L. and Buitelaar, P. (2016) 'An analysis of topic modelling for legislative texts', Proceedings of the Second Workshop on Automated Semantic Analysis of Information in Legal Texts, co-located with the 16th International Conference on Artificial Intelligence and Law (ICAIL 2017), London, UK, 16 June. | en |
| dc.identifier.issn | 1613-0073 | |
| dc.identifier.uri | https://hdl.handle.net/10468/6774 | |
| dc.language.iso | en | en |
| dc.publisher | CEUR Workshop Proceedings | en |
| dc.relation.uri | http://ceur-ws.org/Vol-2143/ | |
| dc.rights | © 2016, the Authors. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). | en |
| dc.subject | Topic modelling | en |
| dc.subject | Dimensionality reduction techniques | en |
| dc.subject | Bayesian inference | en |
| dc.subject | Topic coherency | en |
| dc.title | An analysis of topic modelling for legislative texts | en |
| dc.type | Conference item | en |
