Call for Papers: International Workshop on Mining and Learning in the Legal Domain (MLLD 2021)

The increasing accessibility of large legal corpora and databases create opportunities to develop data driven techniques as well as more advanced tools that can facilitate multiple tasks of researchers and practitioners in the legal domain. While recent advancements in the areas of data mining and machine learning have gained many applications in domains such as biomedical, healthcare and finance, there is still a noticeable gap in how much the state-of-the-art techniques are being incorporated in the legal domain. Achieving this goal entails building a multi-disciplinary community that can benefit from the competencies of both law and computer science experts. The goal of this workshop is to bring the researchers and practitioners of both disciplines together and provide an opportunity to share the latest novel research findings and innovative approaches in employing data analytics and machine learning in the legal domain.

Topics
Following the success of the 1st MLLD workshop (MLLD 2020), the 2nd workshop on Mining and Learning in the Legal Domain (MLLD 2021) discusses a broad variety of topics in various aspects of analyzing legal data such as Legislations, litigations, court cases, contracts, patents, Non-Disclosure Agreements (NDAs) and Bylaws. We encourage submissions on novel mining and learning based solutions in:

• Applications of data mining techniques in the legal domain
• case outcome prediction
• classifying, clustering and identifying anomalies in big corpora of legal records
• legal analytics
• citation analysis for case law
• Applications of natural language processing techniques for legal textual data
• information extraction, information retrieval, question answering and entity extraction/resolution for legal document reviews
• summarization of legal documents
• eDiscovery in legal research
• legal language modelling and legal document embedding and representation
• recommender systems for legal applications
• topic modelling in large amounts of legal documents
• Ethical issues in mining legal data
• privacy and GDPR in legal analytics
• bias in the applications of data mining
• transparency in legal data mining
• Training data for legal domain
• acquisition, representation, indexing, storage, and management of legal data
• automatic annotation and learning with human in the loop
• data augmentation techniques for legal data
• semi-supervised learning, domain adaptation, distant supervision and transfer learning
• Emerging topics in the intersection of data mining and law
• digital lawyers and legal machines
• smart contracts
• future of law practice in the age of AI

Submissions
You are invited to submit your original research and application papers to the workshop. As per ICDM instructions, papers are limited to a maximum of 8 pages, and must follow the IEEE ICDM format requirements. All accepted workshop papers will be published in the formal proceedings by the IEEE Computer Society Press. Each paper is reviewed by at least 3 reviewers from the program committee. Paper review is triple-blind. Manuscripts are to be submitted through CyberChair. More information about the workshop is available here.

Important Dates

• Paper submission due date: September 3, 2021
• Notification of acceptance: September 24, 2021
• Camera ready submission: October 1, 2021
• MLLD -2021 Workshop: December 7, 2021

Thomson Reuters Labs Best Paper Award
Thomson Reuters Labs will generously provide a total of $1000 USD to the best paper(s) submitted (one $1000 award or two $500 awards). The successful paper(s) must have at least one student author, and a student must be cited as the first author. The best paper recipient(s) will be selected by the program committee.

Organizing Committee

• Masoud Makrehchi, OntarioTech University and Thomson Reuters Labs
• Shohreh Shaghaghian, Thomson Reuters Labs
• Ali Vahdat, Thomson Reuters Labs
• Fattane Zarrinkalam, Thomson Reuters Labs