Research

Research Topics

1. KRR for Trustworthy AI, e.g., 

   • Description Logic and Explanation for Ontology and Knowledge Graph applications

     • Similarity-based Reasoning

   • Argumentation and Explanation for Practical Reasoning

     • Analogical Argumentation

   • Human-friendly Explanation Formalisms

   • Implementation of XAI system, e.g., Virtual Knowledge Graph

2. Integration of KRR and ML for Trustworthy AI, e.g., 

   • Knowledge Graph Embedding (i.e. Knowledge Graph meets ML)

   • Ontology Embedding (i.e. Ontology meets ML)

   • Neural-symbolic Learning (i.e. Symbolic Reasoning meets ML)

   • Argument Mining (i.e. Argumentation meets ML)

   • Fairness, Accountability, and Transparency (FAccT)

   • Knowledge-aware Machine Learning

   • Learning Equivalent Whitebox for Explanation Finding

3. Any topics that use either KRR or ML for building AI systems that humans can trust are also welcome! 

Selected Publications

1. Teeradaj Racharak, Watanee Jearanaiwongkul, Khine Myat Thwe, Can Ensemble Calibrated Learning enhance Link Prediction? A Study on Commonsense Knowledge, In LNAI Proceedings of 15th Asian Conference on Intelligent Information and Database Systems (ACIIDS), Thailand, 2023 

2. Teeradaj Racharak, Interpretable Decision Tree Ensemble Learning with Abstract Argumentation for Binary Classification, In Proceedings of the 29th International Conference on Neural Information Processing (ICONIP), New Delhi, India, 2022

3. Teeradaj Racharak, Doing Analogical Reasoning in Dynamic Assumption-based Argumentation Frameworks, In Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Virtual, 2022

4. Kong Wei Kun, Xin Liu, Teeradaj Racharak, Guanqun Sun, Jianan Chen, Qiang Ma, Le-Minh Nguyen, WeExt: A Framework of Extending Deterministic Knowledge Graph Embedding Models for Embedding Weighted Knowledge Graphs, In IEEE Access, vol. 11, pp. 48901-48911, 2023.

5. Wei Kun Kong, Xin Liu, Teeradaj Racharak, Minh Le Nguyen, TransHExt: a Weighted Extension for TransH on Weighted Knowledge Graph Embedding, In Proceedings of the 21st International Semantic Web Conference (ISWC), 2022

6. Wei Kun Kong, Teeradaj Racharak, Yiming Cao, Cheng Peng, Minh Le Nguyen, KGWE: A Knowledge-guided Word Embedding Fine-tuning Model, In Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Virtual, 2021

7. Teeradaj Racharak, Satoshi Tojo, On Explanation of Propositional Logic-based Argumentation System, In Proceedings of 13th International Conference on Agents and Artificial Intelligence (ICAART), Online Streaming, 2021

8. Teeradaj Racharak, On Approximation of Concept Similarity Measure in Description Logic ELH with Pre-trained Word Embedding, In IEEE Access, vol. 9, pp. 61429-61443, 2021. DOI: 10.1109/ACCESS.2021.3073730

For further details, please visit the following pages:

• Homepage (Teeradaj Racharak)

• Google Scholar (Teeradaj Racharak)

• Received Fundings (Teeradaj Racharak)

• ReaLearns's Projects

• ReaLearn's Publication Records