New Frontiers in Artificial Intelligence
Description
This LNAI volume 14644 constitutes the revised selected papers of JSAI-isAI 2023 International Workshops, JURISIN, SCIDOCA, EmSemi and AI-Biz, in Kumamoto, in Japan, held in June 2023.
The 15 full papers included in this volume were carefully reviewed and selected from 52 submissions.
JSAI-isAI 2023 hosted four workshops (JURISIN 2023, SCIDOCA 2023, EmSemi2023, and AI-Biz 2023):
The 17th International Workshop on Juris-informatics (JURISIN 2023) details legal issues from the perspective of information science. It covers various topics, including models of legal reasoning, argumentation agents, legal ontologies, legal knowledge bases, computerized legal education, AI legal problems, legal document analysis, natural language processing for law.
The 7th International Workshop on Scientific Document Analysis (SCIDOCA2023) is an annual international workshop focusing on various aspects and perspectives of scientific document analysis for their effcient use and exploration.
The first International Workshop on Embodied Semiotics (EmSemi2023) focuses on developing a "multimodal semiotic" approach to the existing semiotics discussed in the fields of linguistics and philosophy of language, focusing on the phenomena such as gestures and signs in language interactions, which have not yet been clearly characterized as symbols.
The International Workshop on Artificial Intelligence of and for Business (AI-Biz 2023) focuses on the vast business and AI technology fields. It covers various topics, including investment strategy, Stock market, mergers and acquisitions, online advertisement, knowledge extraction, power market, collaborative multi-agent, visualization, COVID-19 infections, classification, fake news, wide and deep learning.
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Content
- Intro
- Preface
- Organization
- Contents
- JURISIN 2023
- Seventeenth International Workshop on Juris-informatics (JURISIN 2023)
- Compliance Checking in the Energy Domain via W3C Standards
- 1 Introduction
- 2 Background - W3C Standards for the Semantic Web
- 2.1 RDF and OWL
- 2.2 SPARQL and SHACL
- 3 Related Works
- 4 Case Study: Extracting Oil and Gas in Ghana
- 4.1 The (Asserted) Ontology
- 4.2 The SHACL/SPARQL Rules
- 5 Conclusions and Future Works
- References
- Programming Contract Amending
- 1 Introduction
- 2 Background: Modelling Contracts with Stipula
- 3 Amending Contracts
- 4 Stipula with Amendments
- 4.1 Additive Amendment
- 4.2 Overriding Amendment
- 5 Amendment Supplements: Agreements and Constraints
- 6 The Stipula Prototype and its Graphical Interface
- 7 Related Works
- 8 Conclusions
- References
- Modeling Medical Data Access with Prova
- 1 Introduction
- 2 Prova Basics
- 3 Use Case
- 4 Implementation
- 5 Discussion and Related Work
- 6 Conclusions and Future Work
- References
- Improving Vietnamese Legal Question-Answering System Based on Automatic Data Enrichment
- 1 Introduction
- 2 Related Work
- 3 Dataset
- 4 Methods
- 4.1 General Architecture
- 4.2 Indexing
- 4.3 Quickview Retrieval Model
- 4.4 Supervised Model
- 4.5 Ensemble Model
- 5 Experimental Results and Discussion
- 5.1 Quickview Retrieval Result
- 5.2 Supervised Model Results
- 5.3 End-to-End Question Answering System Result
- 6 Conclusions
- References
- Modeling the Judgments of Civil Cases of Support for the Elderly at the District Courts in Taiwan
- 1 Introduction
- 2 Data Source
- 2.1 Open Data of Taiwan Judicial Yuan (TWJY)
- 2.2 Selecting Relevant Documents
- 2.3 A Relevant Social Factor and Mediation
- 3 Problem Definitions and Data Preprocessing
- 3.1 Judgment and Grant Predictions
- 3.2 Preprocessing: Word Segmentation and the Blurring Procedure
- 4 The Grant and Dismiss Decisions
- 4.1 Vectorizations of the Texts: TF-IDF and Sentence-BERT
- 4.2 Classification of the Judgment Documents
- 5 A Model-Tree Approach for Predicting the Grants
- 5.1 Factors Influencing the Grants
- 5.2 Using a Model-Tree Model for Prediction
- 5.3 The Linear and Log-Linear Regression Models
- 5.4 Results of Empirical Evaluations and Ablation Study
- 6 Using NER for Factor Identification
- 7 Concluding Remarks
- Appendix: Finetuning the SBERT
- A.1 Data Preparation
- A.2 Finetuning
- A.3 Results and Discussions
- References
- Using WikiData for Handling Legal Rule Exceptions: Proof of Concept
- 1 Introduction
- 2 Examples from the European Court of Human Rights
- 3 Wikidata
- 4 Framework
- 5 Demonstration
- 6 Discussion
- 6.1 Matching Legal Concepts with Wikidata Items
- 6.2 Exploring Cases Using Sibling Items
- 6.3 Inventing Exceptional Concepts
- 6.4 Restoring Correspondences
- 6.5 Complexity and Validity of Algorithm
- 7 Conclusion
- References
- Constructing and Explaining Case Models: A Case-Based Argumentation Perspective
- 1 Introduction
- 2 Abstract Argumentation for Case-Based Reasoning
- 3 Case Models
- 4 Constructing Case Models
- 5 Explaining Case Models
- 6 Discussion
- 7 Conclusion
- References
- Using Ontological Knowledge and Large Language Model Vector Similarities to Extract Relevant Concepts in VAT-Related Legal Judgments
- 1 Introduction
- 2 Related Works and Motivations
- 3 Methodology
- 4 OntoVAT
- 4.1 Core Concepts
- 4.2 Design and Lexicalisation
- 4.3 Commitment and Scope
- 4.4 Alignment with Upper Ontologies
- 5 Application
- 6 Conclusion
- References
- An Example of Argumentation Scheme from Liability: The Case of Vicarious Liability
- 1 Introduction
- 2 Argumentation Scheme from Vicarious Liability
- 2.1 Vicarious Liability
- 2.2 The Scheme
- 3 Mohamud v. WM Morrison Supermarkets
- 4 Cox v. Ministry of Justice
- 5 Discussion and Limitations
- 5.1 The Relation Between Liability and Causality
- 6 Conclusion
- References
- SCIDOCA 2023
- Seventh International Workshop on Scientific Document Analysis (SCIDOCA 2023)
- Directional Generative Networks
- Comparison to Evolutionary Algorithms, Using Measurements for Molecules
- 1 Introduction
- 2 Related Works
- 3 Directional Generative Networks (DGN)
- 4 Experimental Details
- 4.1 Comparison
- 4.2 Degree of Freedom (DOF) of DGN Input
- 5 Conclusion
- References
- Reference Classification Using BERT Models to Support Scientific-Document Writing
- 1 Introduction
- 2 Related Work
- 3 Creation of Datasets
- 4 Methods
- 4.1 Clustering Method
- 4.2 Evaluation Measures
- 4.3 Experiment 1: Vector-Based Clustering for Abstracts
- 4.4 Experiment 2: Pairwise Learning Based Clustering
- 4.5 Experiment 3: Predicting the Number of Clusters
- 5 Results
- 6 Discussion
- 7 Conclusion and Future Work
- References
- Enhancing Legal Text Entailment with Prompt-Based ChatGPT: An Empirical Study
- 1 Introduction
- 2 Related Work
- 2.1 Introduction to ChatGPT
- 2.2 Approaches to Legal Text Entailment in COLIEE Competition
- 3 Methods
- 3.1 Using ChatGPT API
- 3.2 Prompt-Based ChatGPT for Legal Textual Entailment
- 4 Experimental Results and Error Classification
- 4.1 Experimental Results
- 4.2 Error Analysis and Classification
- 5 Conclusion
- References
- AI-Biz 2023
- Artificial Intelligence of and for Business (AI-Biz 2023)
- 1 The Workshop
- 2 Synopsis of Presented Papers
- 3 Acknowledgment
- Development of a Macroeconomic Simulator with an Elaborated Firm Sector
- 1 Introduction
- 2 Related Works
- 3 Model
- 3.1 Overview of the Model
- 3.2 Flow of Events in a Step
- 3.3 Construction of Business-to-business Supplier-Customer Networks
- 3.4 Demand Matching
- 3.5 Agent Behaviors
- 3.6 Major Differences Between Reference and Current Models
- 4 Simulation Analysis
- 4.1 Analysis Settings
- 4.2 Simulation Results
- 4.3 Sensitivity Analysis
- 5 Summary
- References
- Nowcasting Corporate Product Development Activities Through News Article by BERTopic: The Case of the Japanese Chemical Company
- 1 Background
- 2 Previous Studies
- 3 Analytical Methods
- 3.1 News Data
- 3.2 Extracting News Data
- 3.3 Topic Classification
- 3.4 Comparison with Securities Report
- 4 Result
- 4.1 Result of Extracting News Data
- 4.2 Result of Topic Classification
- 4.3 Comparison with Annual Reports and Production Numbers
- 5 Conclusion
- References
- Do Young People in Regional Cities of Japan Really Shift Away from Owning Automobiles? - From an Empirical Study and a Semi-structured Interview
- 1 Introduction
- 2 Empirical Facts in Yamaguchi Pref. or Related Areas
- 3 A Semi-structured Interview
- 3.1 Hypothesis and Design
- 3.2 Results
- 4 Concluding Remark
- A Statistical Analysis
- References
- Author Index
