[bull-ia] Artificial Intelligence and Law – Special issue « Natural Language Processing for Legal Texts »

Artificial Intelligence and Law – Special issue « Natural Language Processing for Legal Texts »

** Paper submission deadline: March 31st, 2018 **

Guest editors:
Livio Robaldo – University of Luxembourg (Luxembourg)
Serena Villata – Université Côte d’Azur, CNRS, Inria, I3S (France)
Adam Wyner – University of Aberdeen (UK)
Matthias Grabmair – Carnegie Mellon University (US)

—————————————————————-

Legal scholars, practitioners, and government officials are feeling increasingly overwhelmed with the expanding amount of national and international legislation and case law. For example, current European legislation is estimated to be 170,000 pages long, of which over 100,000 pages have been produced in the last ten years. Furthermore, legislation is largely in unstructured formats. The volume and format lead to information overload. As the law becomes more complex, conflicted, and mutable, advanced methodologies are required to mine and reason with legal texts.

The law has always been attractive to language and semantic technology for it is both essential for governing local and global markets and challenging to formalise.
Recent research has highlighted the need to create a bridge between conceptual challenges, such as the role of legal interpretation in mining and reasoning, and computational challenges, such as the handling of big legal data and the complexity of regulatory compliance. To bridge such challenges, several research projects in the legal domain have been recently funded by the EU and similar institutions, among which is  »MIREL: MIning and REasoning with Legal texts ». The aim of the MIREL project is to bridge the gap between the community working on legal ontologies and Natural Language Processing (NLP) methods applied to legal documents, and the community working on reasoning methods and formal logic, towards the objectives described above.

In particular, the volume of legal texts available today means that some kind of Natural Language Processing is needed if this important resource is to be exploited. Some NLP techniques make use of inference. This special issue will address NLP techniques using inference applied to legal texts to perform tasks including, among others, mining arguments, populating ontologies and addressing the problem of multilingualism in legal documents.

The special issue « Natural Language Processing for Legal Texts » welcomes original submissions related but not limited to the following topics, with a special appeal for novel approaches that integrate Natural Language Processing and Reasoning techniques:

– Dialogue and interactive systems for the legal domain
– Discourse and pragmatics for the legal domain
– Generation of legal texts
– Legal information extraction and text mining
– Applications of machine learning in natural language processing of legal text
– Machine translation of legal texts
– Multilinguality for the legal domain
– Information retrieval and question answering for the legal domain
– Resources and evaluation for the legal domain
– Sentiment analysis and argument mining for the legal domain
– Summarization of legal texts
– Tagging, chunking, syntax and parsing on legal texts
– Legal ontology population
– Textual inference and other areas of semantics for the legal domain

*Important Dates*
– Paper submission: 31st March, 2018
– Notification to authors: 30th June, 2018
– Camera-ready: 31st September 2018

*Submission Instructions*
To submit a paper to the special issue, the authors are required to follow the guidelines for manuscript submission of the journal (available here: http://www.springer.com/computer/ai/journal/10506?detailsPage=pltci_2283245). Submissions cannot exceed 25 pages, references included. Each submission will be assigned with two reviewers.

Manuscripts should be submitted online to the Special Issue at http://www.editorialmanager.com/arti/

If have any enquiries/comments, please contact Livio Robaldo at: livio.robaldo@uni.lu
———————————————————————
Desinscription: envoyez un message a: bull-ia-unsubscribe@gdria.fr
Pour obtenir de l’aide, ecrivez a: bull-ia-help@gdria.fr