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AI Approaches to the Complexity of Legal Systems

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Cover of 'AI Approaches to the Complexity of Legal Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction: Legal and Ethical Dimensions of AI, NorMAS, and the Web of Data
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    Chapter 2 RoboPrivacy and the Law as “Meta-Technology”
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    Chapter 3 Revisiting Constitutive Rules
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    Chapter 4 The Truth in Law and Its Explication
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    Chapter 5 From Words to Images Through Legal Visualization
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    Chapter 6 A Petri Net-Based Notation for Normative Modeling: Evaluation on Deontic Paradoxes
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    Chapter 7 Legal Patterns for Different Constitutive Rules
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    Chapter 8 An Architecture for Establishing Legal Semantic Workflows in the Context of Integrated Law Enforcement
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    Chapter 9 Contributions to Modeling Patent Claims When Representing Patent Knowledge
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    Chapter 10 Modeling, Execution and Analysis of Formalized Legal Norms in Model Based Decision Structures
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    Chapter 11 Causal Models of Legal Cases
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    Chapter 12 Developing Rule-Based Expert System for People with Disabilities – The Case of Succession Law
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    Chapter 13 EuroVoc-Based Summarization of European Case Law
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    Chapter 14 Towards Aligning legivoc Legal Vocabularies by Crowdsourcing
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    Chapter 15 Data Protection in Elderly Health Care Platforms
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    Chapter 16 Assigning Creative Commons Licenses to Research Metadata: Issues and Cases
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    Chapter 17 Dataset Alignment and Lexicalization to Support Multilingual Analysis of Legal Documents
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    Chapter 18 A Multilingual Access Module to Legal Texts
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    Chapter 19 Combining Natural Language Processing Approaches for Rule Extraction from Legal Documents
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    Chapter 20 Analysis of Legal References in an Emergency Legislative Setting
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    Chapter 21 Using Legal Ontologies with Rules for Legal Textual Entailment
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    Chapter 22 KR4IPLaw Judgment Miner - Case-Law Mining for Legal Norm Annotation
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    Chapter 23 Towards Annotation of Legal Documents with Ontology Concepts
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    Chapter 24 Reuse and Reengineering of Non-ontological Resources in the Legal Domain
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    Chapter 25 Ontology Modeling for Criminal Law
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    Chapter 26 ContrattiPubblici.org, a Semantic Knowledge Graph on Public Procurement Information
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    Chapter 27 Application of Ontology Modularization for Building a Criminal Domain Ontology
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    Chapter 28 A Linked Data Terminology for Copyright Based on Ontolex-Lemon
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    Chapter 29 Anything You Say May Be Used Against You in a Court of Law
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    Chapter 30 A Machine Learning Approach to Argument Mining in Legal Documents
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    Chapter 31 Answering Complex Queries on Legal Networks: A Direct and a Structured IR Approaches
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    Chapter 32 Inducing Predictive Models for Decision Support in Administrative Adjudication
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    Chapter 33 Arguments on the Interpretation of Sources of Law
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    Chapter 34 Dynamics of the Judicial Process by Defeater Activation
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    Chapter 35 Claim Detection in Judgments of the EU Court of Justice
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    Chapter 36 A Non-intrusive Approach to Measuring Trust in Opponents in a Negotiation Scenario
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    Chapter 37 Network, Visualization, Analytics. A Tool Allowing Legal Scholars to Experimentally Investigate EU Case Law
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    Chapter 38 Electronic Evidence Semantic Structure: Exchanging Evidence Across Europe in a Coherent and Consistent Way
Attention for Chapter 3: Revisiting Constitutive Rules
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Chapter title
Revisiting Constitutive Rules
Chapter number 3
Book title
AI Approaches to the Complexity of Legal Systems
Published by
Springer, Cham, December 2015
DOI 10.1007/978-3-030-00178-0_3
Book ISBNs
978-3-03-000177-3, 978-3-03-000178-0
Authors

Giovanni Sileno, Alexander Boer, Tom van Engers, Sileno, Giovanni, Boer, Alexander, Engers, Tom van, van Engers, Tom

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 50%
Unknown 1 50%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 100%
Student > Master 1 50%
Readers by discipline Count As %
Computer Science 3 150%