A. Abbasi and H. Chen, Writeprints: A stylometric approach to identity-level identification and similarity detection in cyberspace, ACM Transactions on Information Systems (TOIS), vol.26, 2008.

B. Alarie, A. Niblett, and A. Yoon, How artificial intelligence will affect the practice of law, University of Toronto Law Journal, vol.68, pp.106-124, 2018.

N. Aletras, D. Tsarapatsanis, D. Preo?iuc-pietro, and V. Lampos, Predicting judicial decisions of the european court of human rights: A natural language processing perspective, PeerJ Computer Science, 2016.

K. Mário-s-alvim, C. Chatzikokolakis, A. Palamidessi, and . Pazii, Metric-based local differential privacy for statistical applications, 2018.

B. Anandan and C. Clifton, Significance of term relationships on anonymization, Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, vol.03, pp.253-256, 2011.

M. Arrington, AOL Proudly Releases Massive Amounts of Private Data, 2006.

K. D. Ashley and S. Brüninghaus, Automatically classifying case texts and predicting outcomes, Artif. Intell. Law, vol.17, issue.2, pp.125-165, 2009.

D. Kevin, V. Ashley, and . Walker, Toward constructing evidence-based legal arguments using legal decision documents and machine learning, Proceedings of the Fourteenth International Conference on Artificial Intelligence and Law, pp.176-180, 2013.

J. Mikhail, C. J. Atallah, V. Mcdonough, S. Raskin, and . Nirenburg, Natural language processing for information assurance and security: an overview and implementations, Proceedings of the 2000 workshop on New security paradigms, pp.51-65, 2001.

J. Bailey and J. Burkell, Revisiting the open court principle in an era of online publication: Questioning presumptive public access to parties' and witnesses' personal information, Ottawa L. Rev, vol.48, p.143, 2016.

J. Bentham and J. Bowring, The Works of Jeremy Bentham, vol.4, p.1843

S. Brüninghaus and K. D. Ashley, Using machine learning for assigning indices to textual cases, Case-Based Reasoning Research and Development, pp.303-314, 1997.

K. Calamur, In a first for Britain, a secret trial for terrorism suspects. NPR, 2014.

B. Chen, D. Kifer, K. Lefevre, and A. Machanavajjhala, Privacy-preserving data publishing, Trends Databases, vol.2, pp.1-167, 2009.

, Judges Technology Advisory Committee. Open courts, electronic access to court records, and privacy: discussion paper, Canadian Judicial Council, 2003.

A. Conley, A. Datta, H. Nissenbaum, and D. Sharma, Sustaining privacy and open justice in the transition to online court records: A multidisciplinary inquiry, Md. L. Rev, vol.71, p.772, 2011.

T. Custis, F. Schilder, T. Vacek, G. Mcelvain, and H. Alonso, Westlaw Edge AI Features Demo: KeyCite Overruling Risk, Litigation Analytics, and WestSearch Plus, Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law -ICAIL '19, pp.256-257, 2019.

R. Dale, Law and word order: NLP in legal tech, Natural Language Engineering, vol.25, issue.1, pp.211-217, 2019.

, Declaration on Free Access to Law. Declaration on free access to law, 2002.

. Mm-douglass, A. Cliffford, . Reisner, . Long, . Moody et al., De-identification algorithm for free-text nursing notes, Computers in Cardiology, pp.331-334, 2005.

C. Dwork, Languages and Programming -Volume Part II, Proceedings of the 33 rd International Conference on Automata, vol.4052, pp.1-12, 2006.

C. Dwork and M. Naor, Pricing via processing or combatting junk mail, Annual International Cryptology Conference, pp.139-147, 1992.

C. Dwork and A. Roth, The algorithmic foundations of differential privacy, Foundations and Trends® in Theoretical Computer Science, vol.9, issue.3-4, pp.211-407, 2014.

N. Fernandes, M. Dras, and A. Mciver, Generalised differential privacy for text document processing, International Conference on Principles of Security and Trust, pp.123-148, 2019.

C. Finseth, Rfc 1439 uniqueness of unique identifiers, 1993.

C. Fleuriot, Avec l'accès gratuit à toute la jurisprudence, des magistrats réclament l'anonymat. Dalloz Actualité, 2017.

, The call for innovative and open government: an overview of country initiatives, p.9789264107045, 2011.

A. Fouret, M. Perez, V. Barrière, E. Rottier, É. O. Buat-ménard et al., Cour de cassation, 2019.

W. Hartzog and F. Stutzman, The case for online obscurity, Calif. L. Rev, vol.101, p.1, 2013.

F. Hassan, D. Sánchez, J. Soria-comas, and J. Domingo-ferrer, Automatic Anonymization of Textual Documents: Detecting Sensitive Information via Word Embeddings, 2019 18 th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13 th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), pp.358-365, 2019.

J. Jaconelli, Open Justice: A critique of the public trial, 2002.

J. Jacquin, Terrorisme : la peur des magistrats. Le Monde, 2017.

W. Jiang, M. Murugesan, C. Clifton, and L. Si, t-plausibility: Semantic preserving text sanitization, 2009 International Conference on Computational Science and Engineering, vol.3, pp.68-75, 2009.

T. Joachims, Text categorization with support vector machines: Learning with many relevant features, European conference on machine learning, pp.137-142, 1998.

J. Jordon, J. Yoon, and M. Van-der-schaar, PATE-GAN: generating synthetic data with differential privacy guarantees, th International Conference on Learning Representations, ICLR 2019, 2019.

A. Joulin, E. Grave, P. Bojanowski, and T. Mikolov, Bag of tricks for efficient text classification, 2016.

H. Kajino, Y. Baba, and H. Kashima, Instance-privacy preserving crowdsourcing, Second AAAI Conference on Human Computation and Crowdsourcing, 2014.

. Daniel-martin, M. J. Katz, I. I. Bommarito, and J. Blackman, A general approach for predicting the behavior of the supreme court of the united states, PLoS One, vol.12, issue.4, p.2017

M. Kim, J. Rabelo, and R. Goebel, Statute Law Information Retrieval and Entailment, Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law -ICAIL '19, pp.283-289, 2019.

Y. Kim, Convolutional neural networks for sentence classification, 2014.

F. Kort, Quantitative analysis of fact-patterns in cases and their impact on judicial decisions, Harv. L. Rev, vol.79, p.1595, 1965.

S. Lai, L. Xu, K. Liu, and J. Zhao, Recurrent convolutional neural networks for text classification, Twenty-ninth AAAI conference on artificial intelligence, 2015.

P. Liu, X. Qiu, and X. Huang, Recurrent neural network for text classification with multi-task learning, 2016.

A. Mandal, R. Chaki, S. Saha, K. Ghosh, A. Pal et al., Measuring similarity among legal court case documents, Proceedings of the 10 th Annual ACM India Compute Conference, Compute '17, pp.1-9, 2017.

R. S. Max, T. Marques, M. Bianco, T. Roodnejad, C. Baduel et al., Machine learning for explaining and ranking the most influential matters of law, Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law, pp.239-243, 2019.

M. Marrero, J. Urbano, S. Sánchez-cuadrado, J. Morato, and J. M. Gómez-berbís, Named entity recognition: fallacies, challenges and opportunities, Computer Standards & Interfaces, vol.35, issue.5, pp.482-489, 2013.

W. Peter and . Martin, Online access to court records-from documents to data, particulars to patterns, Vill. L. Rev, vol.53, p.855, 2008.

T. Mcclean, Not with a bang but a whimper: The politics of accountability and open data in the uk, APSA 2011 Annual Meeting Paper, 2011.

P. Mcdermott, Building open government, Government Information Quarterly, vol.27, pp.401-413, 2010.

T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean, Distributed representations of words and phrases and their compositionality, Advances in neural information processing systems, pp.3111-3119, 2013.

A. Minocha and N. Singh, Legal document similarity using triples extracted from unstructured text, Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), 2018.

I. Mokanov, D. Shane, and B. Cerat, Facts2law: using deep learning to provide a legal qualification to a set of facts, Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law, pp.268-269, 2019.

M. Mo?ina and J. ?abkar, Argument based machine learning applied to law, Artificial Intelligence and Law, vol.13, issue.1, pp.53-73, 2005.

R. Nallapati, D. Christopher, and . Manning, Legal docket classification: Where machine learning stumbles, Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pp.438-446, 2008.

T. Neal, K. Sundararajan, A. Fatima, Y. Yan, Y. Xiang et al., Surveying stylometry techniques and applications, ACM Computing Surveys (CSUR), vol.50, pp.1-36, 2017.

, How to brief a case, 2009.

M. Opijnen, G. Peruginelli, E. Kefali, and M. Palmirani, On-line publication of court decisions in the EU: Report of the policy group of the project "building on the european case law identifier, 2017.

L. Plamondon, G. Lapalme, and F. Pelletier, Anonymisation de décisions de justice, XIe Conférence sur le Traitement Automatique des Langues Naturelles, pp.367-376, 2004.

S. Praduroux, L. Valeria-de-paiva, and C. Di, Legal tech start-ups: State of the art and trends, Proceedings of the Workshop on MIning and REasoning with Legal texts collocated at the 29 th International Conference on Legal Knowledge and Information Systems, 2016.

P. Quaresma and T. Gonçalves, Using linguistic information and machine learning techniques to identify entities from juridical documents, Semantic Processing of Legal Texts: Where the Language of Law Meets the Law of Language, pp.44-59, 2010.

A. Ratner, H. Stephen, H. Bach, J. Ehrenberg, S. Fries et al., Snorkel: Rapid training data creation with weak supervision, The VLDB Journal, vol.29, issue.2, pp.709-730, 2020.

D. Sanchez, M. Batet, and A. Viejo, Automatic generalpurpose sanitization of textual documents, IEEE Transactions on Information Forensics and Security, vol.8, issue.6, pp.853-862, 2013.

J. Daniel and . Siegel, Cara: An assistance to help find the cases you missed, Law Prac, vol.43, p.22, 2017.

L. Sweeney, Replacing personally-identifying information in medical records, the scrub system, Proceedings of the AMIA annual fall symposium, p.333, 1996.

L. Sweeney, A model for protecting privacy, Int. J. Uncertain. Fuzziness Knowl.-Based Syst, vol.10, issue.5, pp.557-570, 2002.

S. Tan, J. Adebayo, K. Inkpen, and E. Kamar, Investigating hu-man+ machine complementarity for recidivism predictions, 2018.

D. Thenmozhi, K. Kannan, and C. Aravindan, A text similarity approach for precedence retrieval from legal documents, FIRE (Working Notes), pp.90-91, 2017.

B. Weggenmann and F. Kerschbaum, Syntf: Synthetic and differentially private term frequency vectors for privacy-preserving text mining, 2018.

M. Yousfi-monod, A. Farzindar, and G. Lapalme, Supervised machine learning for summarizing legal documents, Advances in Artificial Intelligence, pp.51-62, 2010.

D. Zhang, R. Mckenna, I. Kotsogiannis, M. Hay, A. Machanavajjhala et al., Ektelo: A framework for defining differentiallyprivate computations, Proceedings of the 2018 International Conference on Management of Data, SIGMOD '18, pp.115-130, 2018.

X. Zhang, J. Zhao, and Y. Lecun, Character-level convolutional networks for text classification, Advances in neural information processing systems, pp.649-657, 2015.

J. Zheng, Y. Guo, C. Feng, and H. Chen, A hierarchical neural-network-based document representation approach for text classification, Mathematical Problems in Engineering, 2018.