Legal data mining is the subarea of data mining applied to legal texts, such as legislation, case law, patents, and scholarly works. Legal data mining systems are important to provide easier access to and insights about law for both common persons and legal professionals. This area is becoming increasingly important, because of the rapidly growing volume of legal cases and documents available in digital formats. For this reason, we organized the First International Workshop on Legal Data Analytics and Mining (LeDAM 2018), co-located with ACM CIKM 2018. The website of LeDAM 2018 is https://sites.google.com/site/legaldam2018/. The objectives of the LeDAM 2018 workshop are to: (1) Provide a venue for academic and industrial/governmental researchers and professionals to come together, present and discuss research results, use cases, innovative ideas, challenges, and opportunities that arise from applications of data mining in the legal domain, and (2) Foster collaborations between the Legal and the Artificial Intelligence, Data Mining, Information Retrieval, and Machine Learning communities. The workshop programme included invited talks by the following reputed researchers (see Section 2 for details):
The program also included presentation of papers accepted through the peer-reviewed track (see Section 3), and a panel discussion on emerging problems in legal data mining. We specifically attempted to ensure the presence of both academicians from the data mining/IR/ML communities as well as practitioners from the Law industry among our invited speakers and members of our Program Committee (stated in Section 3). For further details, refer to the LeDAM 2018 website https://sites.google.com/site/legaldam2018/. Copyright © CIKM 2018 for the individual papers by the papers' authors. Copyright © CIKM 2018 for the volume as a collection by its editors. This volume and its papers are published under
The LeDAM 2018 workshop included the following invited talks. • Speaker: Giovanni Sartor, Professor of Legal Informatics and Legal Theory, European University Institute, Italy Title: Using Machine Learning to Support Law Enforcement to the Benefit of Consumers and Data Subject: the CLAUDETTE Project Abstract: The project CLAUDETTE aims to support the detection of potentially unfair and unlawful clause, both in consumer contacts and in privacy policies, through automated tools, based on computational linguistic and artificial intelligence. The purpose is to enable consumer protection bodies and data protection authorities to engage more proactively and efectively in monitoring compliance and in enforcing the law. With regard to both contract terms and privacy policy we have collected a corpus of contract terms, identified diferent kinds of unlawful and unfair terms through legal analysis, and annotated the documents accordingly. Then we have applied and tested diferent computational approaches, including various machine learning algorithms, to detect such terms. The better performing algorithms have been implemented in an application available to the public through the project’s web site. The system is complemented by a crawler, that detects changes in the contract and policies already submitted to the system. • Speaker: Luigi Di Caro, Assistant Professor, Department of Computer Science, University of Turin, Italy Title: Natural Language Processing and Ontology Learning in the Legal Domain Abstract: Legal ontologies aim to provide a structured representation of legal concepts and their interconnections. These ontologies are then exploited to support tasks such as information extraction and question answering in the legal domain. Given the increasing importance of the Web of Data in public administration and in companies, being able to provide machine-readable legal information is becoming a valuable and desired contribution. However, concepts and relations within existing ontologies usually represent limited subjective and application-oriented views of specific subdomains of interest. The talk will discuss resent research on natural language technologies and text mining approaches towards the creation, the reuse and the enrichment of legal ontologies. • Speaker: Jack G. Conrad, Lead Research Scientist, Center for AI and Cognitive Computing, Thomson Reuters, USA Title: 30 Years of AI and Law: Legal Data Analytics in the Long View – Looking Back, Looking Forward Abstract: This talk will begin by examining the roots of Artiifcial Intelligence and Law – including applications involving NLP, data mining, machine learning, and more broadly, data analytics – noting that it has been around for much longer than the recent buzz would suggest. We will explore the field of AI and Law in terms of its development and expansion starting in the 1980s and study how seminal research was conducted and reported on in conference proceedings such as ICAIL and publications such as the AI and Law journal. After having established the foundations of today’s field of AI and Law, we will look to the future and sketch some of the practical application scenarios that the capabilities from the field promise to deliver. These include next-generation tools for legal professionals that can augment their skill sets by providing analytical abilities to help in the crafting of legal strategies. We will illustrate such instruments through the visualization of expected outcomes, while varying key parameters such as trial length, expected costs, and likely award or settlement figures. Lastly, we will investigate the prospective role that prediction tools can play in AI and Law application spaces, while looking still further into the future. 3
• Title: Use of Pseudo Relevance Feedback for Patent Clustering with Fuzzy C-means
Authors: Noushin Fadaei and Thomas Mandl • Title: Argumentation-driven information extraction for online crime reports Authors: Marijn Schraagen, Bas Testerink, Daphne Odekerken and Floris Bex • Title: Deep Ensemble Learning for Legal Query Understanding Authors: Arunprasath Shankar and Venkata Nagaraju Buddarapu 4
We are grateful to the CIKM 2018 workshop chairs Francesco Bonchi and Dimitris Gunopulos for their help and support. We are thankful to all the authors for submitting their papers to our workshop. We thank the PC members for carefully reviewing the papers. Last, but not the least, we are grateful to Paheli Bhattacharya for being the web chair (along with Kripabandhu Ghosh) and keeping the website running and up-to-date.