Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence
School of Business Administration, Southwestern University of Finance and Economics（西南财经大学工商管理学院）；Institute of Systems Engineering, Dalian University of Technology（大连理工大学系统工程研究所）；Business School, Hohai University（河海大学商学院）；Business School, Sichuan University（四川大学商学院）；School of Economics and Management, Southwest Jiaotong University（西南交通大学经济管理学院）；School of Information Management and Statistics, Hubei University of Economics（湖北经济学院信息管理与统计学院）；Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI), University of Granada（格拉纳达大学安达卢西亚数据科学与计算智能研究所）；Faculty of Computing and Information Technology, King Abdulaziz University（阿卜杜勒阿齐兹大学计算机与信息技术学院）
Yuzhu Wu, Zhen Zhang, Gang Kou, Hengjie Zhang, Xiangrui Chao, Cong-Cong Li, Yucheng Dong, Francisco Herrera
Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.
On the Design and Evaluation of Human-centered Explainable AI Systems: A Systematic Review and Taxonomy
Dresden University of Technology（德累斯顿技术大学）；Charité Berlin（柏林夏里特医学院）；Department Speculative Transformation（推测转化部门）；Chair of Engineering Psychology and Applied Cognitive Research（工程心理学与应用认知研究教授职位）
Explainable Artificial Intelligence (XAI) in Computational Pathology: Definitions, Taxonomy, and Recommendations
Indiana University School of Medicine（印第安纳大学医学院）；Indiana University Melvin and Bren Simon Comprehensive Cancer Center（印第安纳大学梅尔文与布伦·西蒙综合癌症中心）；University of Warwick（华威大学）；Emory University（埃默里大学）；Radboud University Medical Center（拉德堡德大学医学中心）；Singapore General Hospital（新加坡中央医院）
Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph
CeADAR - Ireland’s Centre for Applied AI, University College Dublin（爱尔兰应用人工智能中心CeADAR、都柏林大学学院）
Explainable and Interpretable Diabetic Retinopathy Classification Based on Neural-Symbolic Learning
Massachusetts General Hospital（麻省总医院）；Harvard Medical School（哈佛医学院）；Singapore Eye Research Institute（新加坡眼科研究所）；Duke-NUS Medical School（杜克-新加坡国立大学医学院）；Institute for Molecular and Clinical Ophthalmology（分子与临床眼科研究所）；National University of Singapore（新加坡国立大学）
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
TECNALIA；ENSTA, Institute Polytechnique Paris（巴黎综合理工学院ENSTA）；INRIA（法国国家信息与自动化研究所）；University of the Basque Country (UPV/EHU)（巴斯克大学（UPV/EHU））；Basque Center for Applied Mathematics (BCAM)（巴斯克应用数学中心（BCAM））；Segula Technologies（Segula科技公司）；Sorbonne Universitè（索邦大学）；DaSCI Andalusian Institute of Data Science and Computational Intelligence, University of Granada（格拉纳达大学DaSCI安达卢西亚数据科学与计算智能研究所）；Telefonica（西班牙电信公司）
Explainable AI for Safe and Trustworthy Autonomous Driving: A Systematic Review
School of Informatics, University of Edinburgh（爱丁堡大学信息学院）；Institute of Automotive Engineering, Technical University (TU) of Darmstadt（达姆施塔特工业大学汽车工程研究所）；School of Engineering and Physical Sciences, Heriot-Watt University（赫瑞瓦特大学工程与物理科学学院）
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction
University of Gondar（贡德尔大学）；College of Engineering and Applied Science, University of Colorado, Colorado Springs（科罗拉多大学科罗拉多斯普林斯分校工程与应用科学学院）；Can Tho University（芹苴大学）；Ewha Womans University（梨花女子大学）；University of Colorado, Colorado Springs（科罗拉多大学科罗拉多斯普林斯分校）
Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation
Department of CST Tsinghua University Beijing, China（计算机科学与技术系 清华大学 北京中国）；Department of CSE Chandigarh University Mohali, India（计算机科学与工程系 印度昌迪加尔大学 摩哈利）
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges
College of Computer Science and Technology, Zhejiang University（浙江大学计算机科学与技术学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）；School of Software Technology, Zhejiang University（浙江大学软件技术学院）；State Key Laboratory of Blockchain and Security, Zhejiang University（浙江大学区块链与安全国家重点实验室）
Leveraging Taxonomy Similarity for Next Activity Prediction in Patient Treatment
German Reseach Centre for Artificial Intelligence (DFKI), SDS Branch Trier（德国人工智能研究中心（DFKI），特里尔分部）；University of Trier, Business Information Systems II（特里尔大学，商业信息系统二系）
Explainable Artificial Intelligence Techniques for Interpretation of Food Models: a Review
Department of Mathematics, Informatics, and Geosciences University of Trieste（数学、信息学与地质科学系特里斯特大学）；Department of Food Engineering and Technology University of Campinas（食品工程与技术系坎皮纳斯大学）；Faculty of Technology Policy Management University of Technology, Delft（技术政策管理系技术大学，代尔夫特）；ASAC s.r.l., Cessalto (TV), Italy（ASAC公司，Cessalto（TV），意大利）；Department of Food Engineering and Technology, University of Campinas（食品工程与技术系坎皮纳斯大学）
