Unlike usual real graphs which have a low number of edges, we study here a dense network constructed from legal citations. This study is achieved on the simple graph and on the multiple graph associated to this legal network, this allows exploring the behavior of the network structural properties and communities by considering the weighted graph and see which additional information are provided by the weights. We propose new measures to assess the role of the weights in the network structure (...) and to appreciate the weights repartition. Then we compare the communities obtained on the simple graph and on the weighted graph. We also extend to weighted networks the amphitheater-like representation of this legal network. Finally we evaluate the robustness of our measures and methods thus taking into account potential errors which may occur by getting data or building the network. Our methodology may open new perspectives in the analysis of weighted networks. (shrink)

The representation of knowledge in the law has basically followed a rule-based logical-symbolic paradigm. This paper aims to show how the modeling of legal knowledge can be re-examined using connectionist models, from the perspective of the theory of the dynamics of unstable systems and chaos. We begin by showing the nature of the paradigm shift from a rule-based approach to one based on dynamic structures and by discussing how this would translate into the field of theory of law. In order (...) to show the full potential of this new approach, we start from an experiment with NEUROLEX, in which a neural network was used to model a corpus of French Council of State decisions. We examine the implications of this experiment, especially those concerning the limits of the model used, and show that other connectionist models might correspond more adequately to the nature of legal knowledge. Finally, we propose another neural model which could show not only the rules which emerge from legal qualification (NEUROLEX's goal), but also the way in which a legal qualification process evolves from one concept to another. (shrink)

Les avancées rapides dans les technologies numériques ont considérablement changé et amélioré la façon dont les données, informations et outils peuvent être diffusés, gérés, utilisés et réutilisés dans la recherche, et ont créé de nouvelles opportunités pour accélérer le progrès dans la science et l’innovation. Ces développements sont principalement dus au large mouvement formel ou informel de la peer production et à la diffusion globale de l’information mobilisant la coopération de communautés distribuées œuvrant dans des environnements en réseaux. Les initiatives (...) comme celle de Science Commons s’appuient sur un modèle économique de la science évoluant dans un environnement numérique et plus précisément sur un socle de partage et d’échange entre communautés de pairs comme modalité de production. Beaucoup d’autres initiatives de ce type sont en cours . Nous avons choisi Science Commons, dont l’objectif, au-delà de la communication scientifique, vise à accélérer la traduction des données en découverte – en débloquant tous les verrous y compris juridiques qui empêchent que la société bénéficie plus rapidement des résultats scientifiques. La philosophie et les outils pratiques de Science Commons seront décrits comme constitutifs d’une approche résolument ouverte de la connaissance scientifique, dans la lignée de la déclaration de Berlin .Rapid advances in the digital technologies have profoundly changed and improved the way in which data, information and tools can be disseminated, managed, used and re-used in research, and have created new opportunities to speed up progress in science and innovation. These developments are mainly due to an emerging broader movement in support of formal and informal « peer production » and global dissemination of information drawing on the cooperation of distributed science and knowledge communities working in open networked environments. Initiatives like the Science Commons rely on an economic model where science evolves in a digital environment, and more specifically on sharing and exchanges between peer communities as a basis for production. Many other initiatives of this kind are under way . We have chosen the Science Commons, whose objective, over and above scientific communication, is to speed up the translation of data into discovery by removing all barriers, including legal obstacles, that prevent society from enjoying the benefits of scientific results as quickly as possible. The philosophy and practical tools of the Science Commons are described as making up a resolutely open approach to scientific knowledge, as recommended by the Berlin Declaration. (shrink)

We provide a retrospective of 25 years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described in a short subsection individually written by one of the 24 authors. These subsections attempt to place the paper discussed in the context of the development of AI and Law, while often offering some personal reactions and reflections. As a whole, the subsections build into (...) a history of the last quarter century of the field, and provide some insights into where it has come from, where it is now, and where it might go. (shrink)

We explore one aspect of the structure of a codified legal system at the national level using a new type of representation to understand the strong or weak dependencies between the various fields of law. In Part I of this study, we analyze the graph associated with the network in which each French legal code is a vertex and an edge is produced between two vertices when a code cites another code at least one time. We show that this network (...) distinguishes from many other real networks from a high density, giving it a particular structure that we call concentrated world and that differentiates a national legal system (as considered with a resolution at the code level) from small-world graphs identified in many social networks. Our analysis then shows that a few communities (groups of highly wired vertices) of codes covering large domains of regulation are structuring the whole system. Indeed we mainly find a central group of influent codes, a group of codes related to social issues and a group of codes dealing with territories and natural resources. The study of this codified legal system is also of interest in the field of the analysis of real networks. In particular we examine the impact of the high density on the structural characteristics of the graph and on the ways communities are searched for. Finally we provide an original visualization of this graph on an hemicyle-like plot, this representation being based on a statistical reduction of dissimilarity measures between vertices. In Part II (a following paper) we show how the consideration of the weights attributed to each edge in the network in proportion to the number of citations between two vertices (codes) allows deepening the analysis of the French legal system. (shrink)