Background
The rapid expansion of interconnected data ecosystems poses new challenges in knowledge discovery, demanding both adaptability and trustworthiness. As data environments grow in complexity, ensuring reliable and robust discovery processes becomes increasingly critical. Understanding how knowledge patterns emerge and evolve across diverse contexts is essential for developing systems that maintain trustworthiness while adapting to uncertainty. The integration of adaptive and trustworthy knowledge discovery approaches shows immense potential to transform multiple domains, including finance, healthcare, cybersecurity, and industrial automation.
Scope
Modern decision-making processes increasingly rely on dynamic data environments, where both reliability and adaptability are essential. The special session aims to bring together researchers, practitioners, and industry experts to explore recent advances and challenges in adaptive and trustworthy knowledge discovery. We welcome contributions addressing various aspects, including but not limited to:
- Advanced data mining algorithms
- Big data processing and analytics
- Prediction and decision-making
- Knowledge representation and semantic understanding
- Uncertainty quantification and probabilistic modeling
- Privacy & Security in AI systems
- Anomaly detection and clustering
- Federated Learning
- Cross-domain knowledge transfer and generalization
- Applications in various domains (e.g., healthcare, industry, energy)
Submission Information
We welcome original and unpublished research contributions in English that align with the themes of AI-driven data intelligence and trustworthy knowledge discovery.
- Paper Format: All submissions must follow the Submission Guidelines
- Page Limit: Not exceed 15 pages in LNAI format
- Submission System: CMT
- Review Process: Double-blind
- Submission Deadline: 22 May, 2025
- Paper Notification: July 27, 2025
- Camera-ready Deadline: August 10, 2025
- Conference Dates: October 22 to 24, 2025