The 2027 International Conference on the Intersection of Knowledge, Learning, and Reasoning (KLR 2027) is a new international conference dedicated to the methodological intersection of knowledge representation, machine learning, and automated reasoning. KLR 2027 will be held on February 26–28, 2027, in Zhengzhou, China, bringing together researchers from knowledge representation, machine learning, data mining, natural language processing, multi-agent systems, and cognitive computing.
The acquisition, representation, and use of knowledge is a foundational concern of computing, yet it is increasingly fragmented across specialized venues. Knowledge representation and reasoning are addressed in logic and KR communities; machine learning and data mining in KDD and ML venues; knowledge graphs and information systems in CIKM and IS communities; language and perception in NLP and vision venues. KLR exists to provide a dedicated forum for work at the intersection—where knowledge representation meets representation learning, where symbolic reasoning meets data-driven inference, where cognitive learning meets uncertain reasoning. KLR is defined by three complementary keywords: Knowledge, Learning, and Reasoning, and welcomes work in any of these areas and especially at their intersections.
| Full Paper Submission Deadline | December 22, 2026 |
| Notification of Acceptance | January 26, 2027 |
| Final Paper Submission | February 5, 2027 |
| Registration Deadline | February 11, 2027 |
Core topics of interest include, but are not limited to:
Knowledge representation and reasoning
Logic and automated deduction
Knowledge graphs and applications
Constraint satisfaction and search
Uncertainty in reasoning
Web- and knowledge-based information systems
Ontology engineering
Query answering over knowledge bases
Deep learning and representation learning
Machine learning and data mining
Graph theory, graph mining, and graph neural networks
Image processing and analysis
Self-supervised and transfer learning
Knowledge discovery from structured and unstructured data
Evaluation and robustness of learned representations
Submitted papers must be original and not under consideration elsewhere.
Full papers (Word + PDF) should be submitted via the online submission system.
Submit the full paper if both presentation and publication are needed.
Submit the abstract only if you wish to make a presentation without publication.
Please use the official KLR 2027 paper template, available on the conference website.
For any questions, please contact the conference secretariat at contact_klr@163.com.
All papers, both invited and contributed, will be subjected to blind review by at least 2 experts. After a careful reviewing process and presentation at the conference, accepted papers will be published in the conference proceedings by a reputed publisher. Publication arrangements are pending confirmation.
Note: All submitted articles should report original research results, experimental or theoretical, not previously published or under consideration for publication elsewhere. Plagiarism or other misconduct will not be tolerated.
Conference Secretariat: KLR 2027 Organizing Committee
Email: contact_klr@163.com
Phone: +86-17320145218
Address: Zhengzhou 450001, China