KnowLDA 2026 – in the 22nd International Conference on Advanced Data Mining and Applications 2026
Large Language Model
Objective and Topics
This special session focuses on knowledge-enabled large language models for data mining and advanced applications. It aims to bring together researchers and practitioners from machine learning, knowledge representation and reasoning, semantic technologies, and enterprise modelling to explore how these areas can be integrated to develop intelligent information systems for organisational and real-world applications. The session welcomes original and unpublished research contributions on topics including, but not limited to, hybrid AI-reliant information systems, knowledge-enabled LLMs, semantic technologies, data mining, advanced applications, and intelligent information systems.
Potential topics include (but not limited to):
- Hybrid AI-reliant Information Systems
Important Dates
- Paper submission deadline:
June 26, 2026July 26, 2026 - Notification of acceptance: September 2, 2026
- Camera-ready submission deadline: September 11, 2026
- Conference date: November 13-15, 2026
Submission Guidelines
In this special session, we welcome original and unpublished research contributions that align with the themes of Knowledge-Enabled Large Language Models for Data Mining and Advanced Applications.
- Paper Format: All submissions must strictly follow the same specifications, requirements, and policies as the main track submissions in terms of paper length, formatting, and important policies. Please refer to the Submission Guidelines in the main track Call for Papers.
- Page Limit: The maximum length is 15 pages.
- Submission Portal: To submit your paper, you must use the Microsoft CMT site of the ADMA 2026 conference through the track “Knowledge-Enabled Large Language Models for Data Mining and Advanced Applications (KnowLDA 2026)”.
- Double-blind Review: All submissions will undergo a double-blind peer review process, ensuring that author identities and affiliations remain anonymous to the reviewers, authors submit blinded manuscripts without identifying information, and reviewers and authors avoid any de-anonymization attempts. The quality of this special session will be ensured by having each contribution reviewed by at least two or three experts in the field.
Published Guidelines
The papers will be published in proceedings in Springer LNBIP series.
Technical Program Committee
- Xungang Gu, Deakin University, Australia
- Yangjie Tian, Victoria Univeristy, Australia
- Saad Masood, Swinburne University of Technology, Australia
- Muhammad Wahid Akram, Deakin University, Australia
- Muhammad Absar Uddin, Atlantic Technological University, Ireland
- Muhammad Yunis Daha, Ulster University, Belfast, UK
- Thuseethan Selvarajah, Charles Darwin University, Australia
- Tianhao Yu, Charles Darwin University, Australia
- Rongsheng Li, Harbin Engineering University, China
- Tianxing Wu, Southeast University, China
- Jie Ma, Xidian University, China
- Sha Hu, Southwest University, China
Organizing Committee
