General Track Sessions

Papers may be submitted to one of the following General Tracks, or to an Invited Session. Only make one submission and select the track or session which best matches the topic of the paper.

The General Tracks are as follows:-

Generic Tracks

G1: Machine Learning, Artificial Neural Networks and Deep Learning

This track will cover both machine learning theoretical research and its applications. Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning in different application fields with especial emphasis on the design of those systems, are particularly encouraged.

The topics of interest include (but are not limited to):

computational learning theory
cooperative learning
federated Learning and distributed IA
distributed and parallel learning algorithms and applications
feature extraction and classification
hybrid learning algorithms
inductive learning
instance-based learning
knowledge discovery in databases
knowledge intensive learning
learning through mobile data mining
machine learning and information retrieval
machine learning for web navigation and mining
multi-strategy learning
neural network learning
online and incremental learning
reinforcement learning
scalability of learning algorithms
statistical learning
text and multimedia mining through machine learning
machine learning for natural language processing

Chair: Prof Ahmed Samet INSA Strasbourg, France

G2: Knowledge Based and Expert Systems

This track covers knowledge-based systems and expert systems, both theoretical research and its applications. Contributions using techniques in knowledge-based systems and expert systems applied to real-world problems, as well as interdisciplinary research involving knowledge-based systems and expert systems in different application fields, are particularly encouraged.

The topics of interest include (but are not limited to):

Knowledge-Based Systems and Expert systems
Knowledge Management and Decision-Support Systems
Knowledge Engineering and Modelling
Knowledge Acquisition, Knowledge Elicitation and Negotiation
Knowledge Representation and Decision Making, Knowledge Preferences, Causality, Decision/Utility Theory, Probabilistic Inference, Relational Probabilistic Models, Sequential Decision Making, Stochastic Optimization,
Uncertainty Representations, Uncertainty in AI, Bayesian Networks
Reasoning and Reasoning strategies: Ontologies Reasoning, Automated Reasoning, Case-Based Reasoning, Common-Sense Reasoning, Computational Complexity of Reasoning, Description Logics, Diagnosis and Abductive Reasoning, Nonmonotonic Reasoning, Qualitative Reasoning, and Reasoning with Beliefs
Tools, and Methodologies for Representing, Managing, and Visualizing contents and decision-making
Visualization and Graphical Models

Other topics of interest are (but are not limited to):

E-Learning, E-Business, E-Commerce Web Intelligence, Intelligent Web-based Systems
Web Personalization and User Modeling AI Web systems: Data Analytics, Multimedia and Multimodal Web Applications
Web Services: Semantic Descriptions, Planning, Matching, and Coordination, Web-Based Collaboration and Cooperation Crowdsourcing Techniques and Methodologies Web Search and Information Retrieval
Open Data Human Language Technologies for Web Systems
Text Summarization and Machine Translation Intelligent User Interfaces for Web Systems
Knowledge Acquisition from the Web Languages
Semantic Web Data Searching, Querying
Visualizing, and Interpreting the Semantic Web Social Networking and Community Identification
Web-Based Recommendation Systems, Web-Based Opinion Extraction and Trend Spotting.

Chair: Prof Anne Hakansson Royal Institute of Technology, Sweden

G3: Intelligent Information and Engineering Systems

G3 track covers both intelligent information and engineering systems (G3a) and Cybersecurity (G3b), theoretical research and applications.

Intelligent information and engineering systems is a broad topic and includes contributions describing techniques handling real-world problems. It also includes research involving intelligent information and engineering in different application fields.

The topics of interest include (but are not limited to):

Natural Language Processing
Agent and Multi-Agent Systems
Bio-inspired Systems
Nature Inspired Methods and Optimization
Image Processing and Signal Processing
Machine & Computer Vision
Monitoring and Prediction
Speech Processing and Synthesis

Chair: Prof Ron Hartung Franklyn University, United States

G4: Industry Applications

This track covers Industry Applications. Contributions describing industry application techniques applied to real-world problems and interdisciplinary research involving industry applications in different application fields, with especial emphasis on industry, are particularly encouraged.

Multi-Sensor Information Systems
Dimensionality Reduction and Interactive Multivariate Data Visualization/Analysis
Organisation Memories
Industrial Control
Fault Diagnosis
Image Processing
Medical & Diagnostic Systems
Environmental Monitoring
Power Electronics & Drives, High Voltage Systems
Robotics
Engine Control and Vehicle Applications, Smart Vehicles and AGVs, Signal and Time Series Processing
Wavelets
Industrial communication standards (OPCUA, MqTT, DDS), Minifactories
Industry 4.0 applications, Financial & Stock Market
Dashboards, real time networking
Time Sensitive Networks, Industrial Wireless (5G, ZigBee)

Chair: Dr Carlos Toro - ARTC (Advanced Remanufacturing and Technology Centre) - A*Star (Singapore)

Thematic Tracks

T1: Knowledge-based Decision Making

The aim of the track is to gather the entire decision making (DM) oriented research, including academic and practically-oriented researchers and decision-makers. The conference will provide a platform for interdisciplinary discussions oriented on decision analysis, behavioral economics, judgment and decision-making, machine learning, statistics and other related topics and disciplines. The papers may address various theoretical and practical areas of DM. Contributions addressing knowledge-based DM and reasoning are especially welcome.
The main goal of the session is to attract researchers from all over the world, who will present their theoretical and applied contributions in the areas including, but not limited to:

Advances in DM theories and practices
Multi Criteria Decision Analysis (MCDA) foundations, development and applications
Knowledge extraction in DM
Knowledge bases and ontologies in DM
Group DM and Negotiations
Computing and Software supporting knowledge-based DM
Theories, methods and techniques of handling uncertainty in DM

Chairs:
Prof Jaroslaw Watrobski, University of Szczecin, Poland
Dr. Wojciech Salabun, West Pomeranian University of Technology in Szczecin, Poland

** PLEASE NOTE:
- Do not submit the same paper to more than one General Track or Invited Session as they may be deleted from the conference.
- We may re-allocate papers to more appropriate tracks if we feel it necessary.