China Conference on Knowledge Graph and Semantic Computing (CCKS 2025)
Conference Dates: September 19–21, 2025
Conference Website: https://sigkg.cn/ccks2025/

The China Conference on Knowledge Graph and Semantic Computing (CCKS) is organized by the Technical Committee on Language and Knowledge Computing of the Chinese Information Processing Society of China. The conference originated from the Chinese Knowledge Graph Symposium (CKGS) and the Chinese Semantic Web and Web Science Conference (CSWS), which were merged in 2016. From 2016 to 2024, CCKS has been held in Beijing, Chengdu, Tianjin, Hangzhou, Nanchang, Guangzhou (online), Qinhuangdao, Shenyang, and Chongqing.

CCKS has become a core academic conference in China in the fields of knowledge graphs and semantic technologies, attracting researchers and developers in knowledge representation and reasoning, natural language understanding and knowledge acquisition, graph data management and computing, intelligent question answering, and more.

CCKS 2025 will be held in Fuzhou from September 19 to 21, 2025.

The theme of this year’s conference is “Large Model Agents and Knowledge Computing”. It aims to explore how large model agents can improve their accuracy and reliability in knowledge computing with the support of knowledge graphs. The conference will focus on key technologies such as knowledge representation, storage, mining, fusion, reasoning, explainability, ethics, knowledge graph-enhanced large models, and agent architectures. The goal is to guide paradigm shifts in knowledge computing and promote the development of knowledge-enhanced large model agents.

The program will feature tutorials, keynote talks, frontier forums, industry forums, young scholar forums, evaluations and competitions, paper presentations, posters, and system demonstrations. Distinguished scholars and industry leaders will be invited to share the latest developments and foster academic-industry collaboration.

Open Resource Track

In addition to research and application papers, CCKS 2025 will include a special track on Open Resources for Knowledge Graphs, aiming to promote data and resource sharing across academia and industry. Resources may include (but are not limited to): knowledge graphs/ontologies, datasets/evaluation sets, software tools/services/APIs/frameworks, protocols/standards, etc. Contributions to the OpenKG community are highly encouraged.

Submissions will be evaluated based on resource quality and impact, reusability (e.g., documentation), and accessibility (e.g., URLs and open-source licenses). Selected resources will be promoted through the OpenKG platform.

We sincerely invite researchers and practitioners to submit original, unpublished papers in either English or Chinese.

  • English paper: max 12 pages (PDF, including references and appendices)
  • Chinese paper: max 8 pages (PDF, including references and appendices)

Review Process:

  • Research & application papers: double-blind review (no author information anywhere in the submission)
  • Open resource papers: single-blind review (include author info and resource URL)

Templates:

Accepted English papers will be published in the Springer LNCS proceedings. Outstanding papers may be invited to submit extended versions to journals such as Tsinghua Science and Technology, Journal of Computer Science and Technology, and Data Intelligence.

Accepted Chinese papers will be recommended to journals such as Journal of Tsinghua University (Science and Technology), Journal of Chinese Information Processing, and Journal of Peking University, subject to further review by the journals.

Topics of Interest (include but are not limited to):

  • Knowledge representation and reasoning over knowledge graphs (e.g., ontology modeling and evolution, KG embedding, KG completion)
  • Knowledge graph construction and integration (e.g., entity/event extraction, complex/multimodal knowledge acquisition, ontology matching, entity alignment)
  • Graph databases and knowledge management (e.g., graph DB architecture, query languages, indexing, knowledge management applications)
  • Large models enhanced by knowledge graphs (e.g., KG-enhanced training/inference, explainability)
  • Applications of knowledge graphs and large models/agents (e.g., semantic search, QA/dialogue, retrieval-augmented generation, agent architectures, applications in government, science, education, healthcare)
  • Open resources for knowledge graphs and large models (e.g., domain-specific KGs/LMMs, benchmarks, tools)

Submission Site

https://openreview.net/group?id=cipsc.org/CCKS/2025/Conference

Important Dates

  • Full Paper Submission Deadline: June 30, 2025 (23:59 Beijing Time)
  • Notification of Acceptance: July 30, 2025 (23:59 Beijing Time)
  • Camera-Ready Submission Deadline: August 10, 2025 (23:59 Beijing Time)

For submission inquiries, please contact: ccks2025@gmail.com