Table of Content

Transfroming from Data to Knowledge and Applications in Intelligent Systems

Submission Deadline: 01 November 2023 Submit to Special Issue

Guest Editors

Dr. Hien D. Nguyen, University of Information Technology, VNU-HCM, Vietnam.
Prof. Yucong Duan, Hainan University, China.
Prof. Enrique-Herrera Viedma, University of Granada, Spain.

Summary

Nowadays there have been many research and applications in data science and knowledge engineering for modern daily lives. With the development of new technologies, smart systems have become more useful and be applied in a wide range of areas, including industry, education, healthcare, computer vision, software engineering, fintech, and administrator management.


Intelligent systems have been created to better serve the increasing needs of people. Those systems require a knowledge base to become more intelligent and acceptable in the real-world. Knowledge Engineering studies the methods for Knowledge Representation and Reasoning, which are exciting and well-established fields of research in designing knowledge bases for intelligent systems. Knowledge engineering has derived challenges from new and emerging fields including the semantic web, computational biology, and the development of software agents. It is also the foundation for building potential technologies of intelligent software.


The main objective of this Special Issue is to highlight the technologies in knowledge engineering anddata science. Those techniques tend to apply in the real-world, especially intelligent systems for real-world applications. It also discusses and exchanges recent innovations, developments and challenges in knowledge representation, automated reasoning and hybrid intelligent systems, such as, using knowledge base, big data, machine learning, etc. for application in industry, engineering, science, industry, automation & robotics, business & finance.


Keywords

We welcome authors to present new techniques, methodologies, mixed method approaches and research directions unsolved issues. Topics of interest include, but are not limited to:
Data Mining and Knowledge Discovery
Domain Analysis and Knowledge Modeling
Data Engineering
Database technology for AI
Spatial Databases and Temporal Databases
Cloud data management
Knowledge Management
Knowledge Representation
Ontology Engineering
Domain Ontologies
Ontology Matching and Alignment
Ontology Sharing and Reuse
Enterprise Ontology
Semantic Web
Intelligent tutoring system
Intelligent Problem Solver
Intelligent Information Systems
Expert systems
Decision Support Systems
Document Retrieval Systems
Human-Machine Cooperation
Social network and Information Diffusion
Intelligent software in education, healthcare, business, etc.

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