会議情報
DIKW 2023: IEEE International Conference on Data, Information, Knowledge and Wisdom
http://www.swinflow.org/confs/2023/dikw/
提出日:
2023-08-25
通知日:
2023-10-15
会議日:
2023-12-17
場所:
Melbourne, Australia
年:
1
閲覧: 3659   追跡: 1   出席: 1

論文募集
Introduction

Data, Information, Knowledge and Wisdom, in short (DIKW), have been used widely as marking terms in various domains for expressing and exchanging semantic or conceptual subjective or objective understandings. However, there are still no unified understandings over the meaning of the DIKW concepts. Data, Information, Knowledge, and Wisdom as a whole concept of DIKW is also missing unified understandings of the relationships among them. Therefore, there have been proposals and models of DIKW as “layered hierarchy”, “architecture”, “framework”, “network”, “thinking mode”, “pattern”, “style”, “theory”, “methodology”, “model”, “graph”, etc.

2023 International Conference on Data, Information, Knowledge and Wisdom (DIKW 2023) aims to bring together scientists, researchers, and industrial engineers to exchange experimental and theoretical Data/Information/Knowledge/Wisdom modeling and processing results, novel designs, explainable AI, AI governance, work-in-progress and case studies on theories, design mechanisms and extensions on DIKW transformations and interactions in all areas, in all phases, empirical or theoretical solutions.

Scope and Topics

Topics of particular interest include, but are not limited to:

- Theories, Algorithms and Platforms for Data Analytics and Information Retrieving
- Data Provenance, Cleaning, Curation and Governance Services
- Data, Information, Knowledge and Wisdom Sharing, Integration and Migration
- Real-time Data Modeling and Information Provision Services and Applications
- Data-driven Intelligent Decision-making and Innovative Applications
- Goal or Purpose Models, Techniques and Tools for Smart Computing
- Data Models, Information Semantics, Query languages
- Data Stream Systems and Sensor Networks
- Data Visualization and Interactive Data Exploration
- Hybrid AI Privacy, Security, Trust, and Responsibility Provision
- Data-Knowledge Mixed Processing Systems and Service Architecture
- Domain Knowledge Modeling and Ontology-Building
- Data, Information and Knowledge Transformation Load balance
- DIKW content Storage and Retrieval and Interface Technology
- Software Tools for Data-Information-Knowledge Quality Modeling and Testing
- Computational Intelligence for Data, Information and Knowledge Hybrid Systems
- Multimedia and Cross-modals "Databases" Processing
- Development and Management of Heterogeneous Knowledge Bases
- Knowledge Extraction, Discovery, Analysis and Representation
- Application of Knowledge Representation Techniques to Semantic Modeling
- Optimization Techniques of DIKW applications
- Theories of DIKW Models and Performance Evaluation Approach
最終更新 Dou Sun 2023-07-16
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関連仕訳帳
CCF完全な名前インパクト ・ ファクター出版社ISSN
ACM Journal of Data and Information QualityACM1936-1955
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