[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122243-en":3,"doc-seo-122243-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122243,1374391975076,"Riley","https://ap-avatar.wpscdn.com/avatar/14000253ca4ec9f6853?x-image-process=image/resize,m_fixed,w_180,h_180&k=1783305029341752051",8,"Research & Report","Machine Learning Solutions for Improving Access to Law - Doctoral Thesis","Many individuals encounter legal disputes, yet limited legal literacy often leaves people with few resources vulnerable. This doctoral thesis examines how machine learning and natural language processing can bridge that gap via automated legal aid systems. It studies automated retrieval of relevant legislation and the generation of understandable answers to layperson legal questions. The work addresses dataset scarcity and evaluates multiple information-retrieval approaches and a newly introduced question–legislation dataset.","Machine learning solutions for improving access to law  \nCitation for published version (APA):  \nLouis, A. (2025) . Machine learning solutions for improving access to law. [Doctoral Thesis, Maastricht University] . [https://doi.org/10.26481/dis.20250519al](https://doi.org/10.26481/dis.20250519al)  \nDocument status and date:  \nPublished: 19/05/2025  \nDOI:  \n10.26481/dis.20250519al  \nDocument Version:  \nPublisher's PDF, also known as Version of record  \nPlease check the document version of this publication:  \n• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.  \n• The final author version and the galley proof are versions of the publication after peer review.  \n• The final published version features the final layout of the paper including the volume, issue and page numbers.  \nLink to publication  \nGeneral rights  \nCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.  \n• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  \n• You may not further distribute the material or use it for any profit-making activity or commercial gain  \n• You may freely distribute the URL identifying the publication in the public portal.  \nIf the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, please follow below link for the End User Agreement:  \n[www.umlib.nl/taverne-license](www.umlib.nl/taverne-license)  \nTake down policy  \nIf you believe that this document breaches copyright please contact us at:  \n[repository@maastrichtuniversity.nl](repository@maastrichtuniversity.nl)  \nproviding details and we will investigate your claim.  \nDownload date: 02 Jun. 2025  \nMACHINE LEARNING-OPLOSSINGEN VOOR BETERE TOEGANG TOT HET RECHT  \nMACHINE LEARNING SOLUTIONS FOR IMPROVING ACCESS TO LAW  \nMACHINE LEARNING SOLUTIONS FOR IMPROVING ACCESS TO LAW  \nDissertation  \nto obtain the degree of Doctor at the Maastricht University, on the authority of the Rector Magnificus, Prof. Dr. Pamela Habibovi in accordance with the decision of the Board of Deans, to be defended in public on Monday, 19 May 2025, at 16:00 hours  \nby  \nANTOINE LOUIS  \nSupervisors:  \nProf. Dr. G. van Dijck (Maastricht University)  \nDr. G. Spanakis (Maastricht University)  \nAssessment Committee:  \nProf. Dr. A. Kamperman Sanders (Chair, Maastricht University)  \nProf. Dr. F.J. Bex (Utrecht University/Tilburg University)  \nProf. Dr. J.E.B. Coster van Voorhout (Maastricht University/VU Amsterdam) Prof. Dr. M. Grabmair (Technical University of Munich)  \nProf. Dr. J. Scholtes (Maastricht University)  \nThis research is partially supported by the Sector Plan Digital Legal Studies of the Dutch Ministry of Education, Culture, and Science. In addition, this research was made possible, in part, using the Data Science Research Infrastructure (DSRI) hosted at Maastricht University.  \nKeywords: Machine Learning, Natural Language Processing, Information Retrieval, Question Answering, Specialized Domain, Access to Law  \nPrinted by: [Print Service Ede-](Print Service Ede-www.proefschriftenprinten.nl)[www.proefschriftenprinten.nl](Print Service Ede-www.proefschriftenprinten.nl)  \n[ISBN 978-90-835486-0-9](ISBN 978-90-835486-0-9)  \nCopyright© 2025, Antoine Louis, Maastricht, The Netherlands  \nAn electronic version of this dissertation is available at  \n[https://cris.maastrichtuniversity.nl/en/publications/](https://cris.maastrichtuniversity.nl/en/pub","cbCaipJ93JwNT0ga","https://ap.wps.com/l/cbCaipJ93JwNT0ga","pdf",11292944,1,163,"English","en",105,"# Summary\n## Research focus and motivation\n## Automated legal aid and answer generation\n## Information retrieval effectiveness (Chapter 2)\n## Dataset construction and benchmarking","[{\"question\":\"What problem does the thesis target in access to justice?\",\"answer\":\"The thesis targets the legal literacy gap that can make individuals vulnerable during disputes. It explores automated legal aid to help laypeople navigate complex legal issues.\"},{\"question\":\"How does the thesis evaluate retrieving relevant legislation?\",\"answer\":\"It assesses modern information retrieval approaches for answering simple legal questions. Benchmarking on a dedicated dataset compares retrieval methods and highlights strong performance of fine-tuned dense neural models.\"},{\"question\":\"What dataset is introduced to support the research?\",\"answer\":\"The thesis introduces a dataset containing over 1,100 open-ended questions across legal topics. Experienced jurists annotate these questions with pertinent legislation drawn from an evidence corpus of more than 22,600 law articles.\"}]","Machine Learning Solutions for Improving Access to Law - Doctoral Thesis | PDF",1785809610,411,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-solutions-for-improving-access-to-law-doctoral-thesis","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-solutions-for-improving-access-to-law-doctoral-thesis/122243/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the thesis target in access to justice?","Question",{"text":75,"@type":76},"The thesis targets the legal literacy gap that can make individuals vulnerable during disputes. 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