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  1.  12
    Eveline T. Feteris: Fundamentals of Legal Argumentation.T. J. M. Bench-Capon - 2018 - Artificial Intelligence and Law 26 (3):307-314.
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  2.  5
    Norms Modeling Constructs of Business Process Compliance Management Frameworks: A Conceptual Evaluation.Mustafa Hashmi & Guido Governatori - 2018 - Artificial Intelligence and Law 26 (3):251-305.
    The effectiveness of a compliance management framework can be guaranteed only if the framework is based on sound conceptual and formal foundations. In particular, the formal language used in the CMF is able to expressively represent the specifications of normative requirements that impose constraints on various activities of a business process. However, if the language used lacks expressiveness and the modelling constructs proposed in the CMF are not able to properly represent different types of norms, it can significantly impede the (...)
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  3.  2
    Dynamic Epistemic Logic of Belief Change in Legal Judgments.Pimolluck Jirakunkanok, Katsuhiko Sano & Satoshi Tojo - 2018 - Artificial Intelligence and Law 26 (3):201-249.
    This study realizes belief/reliability change of a judge in a legal judgment by dynamic epistemic logic. A key feature of DEL is that possibilities in an agent’s belief can be represented by a Kripke model. This study addresses two difficulties in applying DEL to a legal case. First, since there are several methods for constructing a Kripke model, our question is how we can construct the model from a legal case. Second, since this study employs several dynamic operators, our question (...)
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  4.  14
    Automated Patent Landscaping.Aaron Abood & Dave Feltenberger - 2018 - Artificial Intelligence and Law 26 (2):103-125.
    Patent landscaping is the process of finding patents related to a particular topic. It is important for companies, investors, governments, and academics seeking to gauge innovation and assess risk. However, there is no broadly recognized best approach to landscaping. Frequently, patent landscaping is a bespoke human-driven process that relies heavily on complex queries over bibliographic patent databases. In this paper, we present Automated Patent Landscaping, an approach that jointly leverages human domain expertise, heuristics based on patent metadata, and machine learning (...)
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  5.  11
    Introduction to the Special Issue on Legal Text Analytics.Jack G. Conrad & L. Karl Branting - 2018 - Artificial Intelligence and Law 26 (2):99-102.
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  6.  8
    Bending the Law: Geometric Tools for Quantifying Influence in the Multinetwork of Legal Opinions.Greg Leibon, Michael Livermore, Reed Harder, Allen Riddell & Dan Rockmore - 2018 - Artificial Intelligence and Law 26 (2):145-167.
    Legal reasoning requires identification through search of authoritative legal texts that apply to a given legal question. In this paper, using a network representation of US Supreme Court opinions that integrates citation connectivity and topical similarity, we model the activity of law search as an organizing principle in the evolution of the corpus of legal texts. The network model and probabilistic search behavior generates a Pagerank-style ranking of the texts that in turn gives rise to a natural geometry of the (...)
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  7.  18
    Recurrent Neural Network-Based Models for Recognizing Requisite and Effectuation Parts in Legal Texts.Truong-Son Nguyen, Le-Minh Nguyen, Satoshi Tojo, Ken Satoh & Akira Shimazu - 2018 - Artificial Intelligence and Law 26 (2):169-199.
    This paper proposes several recurrent neural network-based models for recognizing requisite and effectuation parts in Legal Texts. Firstly, we propose a modification of BiLSTM-CRF model that allows the use of external features to improve the performance of deep learning models in case large annotated corpora are not available. However, this model can only recognize RE parts which are not overlapped. Secondly, we propose two approaches for recognizing overlapping RE parts including the cascading approach which uses the sequence of BiLSTM-CRF models (...)
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  8.  9
    Automatic Semantic Edge Labeling Over Legal Citation Graphs.Ali Sadeghian, Laksshman Sundaram, Daisy Zhe Wang, William F. Hamilton, Karl Branting & Craig Pfeifer - 2018 - Artificial Intelligence and Law 26 (2):127-144.
    A large number of cross-references to various bodies of text are used in legal texts, each serving a different purpose. It is often necessary for authorities and companies to look into certain types of these citations. Yet, there is a lack of automatic tools to aid in this process. Recently, citation graphs have been used to improve the intelligibility of complex rule frameworks. We propose an algorithm that builds the citation graph from a document and automatically labels each edge according (...)
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  9.  5
    Network Approach to the French System of Legal Codes Part II: The Role of the Weights in a Network.Romain Boulet, Pierre Mazzega & Danièle Bourcier - 2018 - Artificial Intelligence and Law 26 (1):23-47.
    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 (...)
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  10.  6
    Research in Progress: Report on the ICAIL 2017 Doctoral Consortium.Maria Dymitruk, Réka Markovich, Rūta Liepiņa, Mirna El Ghosh, Robert van Doesburg, Guido Governatori & Bart Verheij - 2018 - Artificial Intelligence and Law 26 (1):49-97.
    This paper arose out of the 2017 international conference on AI and law doctoral consortium. There were five students who presented their Ph.D. work, and each of them has contributed a section to this paper. The paper offers a view of what topics are currently engaging students, and shows the diversity of their interests and influences.
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  11.  8
    Representing Dimensions Within the Reason Model of Precedent.Adam Rigoni - 2018 - Artificial Intelligence and Law 26 (1):1-22.
    This paper gives an account of dimensions in the reason model found in Horty : 1–33, 2011), Horty and Bench-Capon and Rigoni :133–160, 2015. doi: 10.1007/s10506-015-9166-x). The account is constructed with the purpose of rectifying problems with the approach to incorporating dimensions in Horty, namely, the problems arising from the collapse of the distinction between the reason model and the result model on that approach. Examination of the newly constructed theory revealed that the importance of dimensions in the reason model (...)
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