An analysis of topic modelling for legislative texts

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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.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 http://hdl.handle.net/10468/6774
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.format.mimetype application/pdf en
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
dc.internal.authorcontactother Leona O’Brien, Governance, Risk and Compliance Technology Centre, University College Cork, Cork, Ireland. T: +353-21-490-3000 E: leona.obrien@ucc.ie en
dc.internal.availability Full text available en
dc.description.version Accepted Version en
dc.description.status Peer reviewed en


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