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CIKM 2025 : Conference on Information and Knowledge Management

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Conference Series : Conference on Information and Knowledge Management
 
Link: https://cikm2025.org/
 
When Nov 10, 2025 - Nov 14, 2025
Where Seoul, Republic of Korea
Abstract Registration Due May 16, 2025
Submission Deadline May 23, 2025
Notification Due Aug 4, 2025
Final Version Due Aug 27, 2025
 

Call For Papers

The Conference on Information and Knowledge Management (CIKM) provides a unique venue for industry and academia to present and discuss state-of-the-art research on artificial intelligence, search and discovery, data mining, and database systems, all at a single conference. CIKM is uniquely situated to highlight technologies and insights that materialize the big data and artificial intelligence vision of the future. CIKM 2025 will take place between Nov 10-14, 2025 in Coex, Seoul, Korea.

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Key Dates
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All deadlines are at 11:59pm in the Anywhere on Earth (AoE) time zone.
• Full Papers Abstract Deadline: May 16, 2025
• Full Papers Final Deadline: May 23, 2025
• Papers Notifications: August 4, 2025
• Camera Ready Deadline: August 27, 2025

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Topics of Interest
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We encourage submissions of high-quality research papers on the general areas of artificial intelligence, data science, databases, information retrieval, and knowledge management. Topics of interest include, but are not limited to, the following areas:
• Data acquisition and processing (e.g., IoT Data, Data Quality, Data Privacy, Mitigating Biases, Data Wrangling, Data exploration, Data Preparation, Valuation, and Trading)
• Data Integration and aggregation (e.g., Semantic Processing, data provenance, data linkage, data fusion, knowledge graph, data warehousing, data lake, privacy and security, modeling, information credibility)
• Efficient data processing (e.g., serverless, data-intensive computing, database systems, indexing and compression, architectures, distributed data systems, dataspaces, customized hardware)
• Special data processing (e.g., multilingual text, sequential, stream, time series, spatio-temporal, (knowledge) graph, multimedia, scientific, and social media data)
• Analytics and machine learning (e.g., OLAP, data mining, machine learning and AI, scalable analysis algorithms, algorithmic biases, event detection and tracking, algorithmic interpretability)
• Neural Information and knowledge processing (e.g., graph neural networks, domain adaptation, transfer learning, network architectures, neural ranking, neural recommendation, and neural prediction)
• Information access and retrieval (e.g., Information Retrieval with Large Language Models, Question Answering and Dialogue Systems, Open-ended Question Answering Systems, Generation of Knowledge Graphs from Unstructured data, Retrieval Models, Query Processing, Personalization, Recommender Systems, Filtering Systems)
• Users and interfaces for information systems (e.g., user behavior analysis, user interface design, perception of biases, interactive information retrieval, interactive analysis, spoken interfaces)
• Evaluation (e.g., performance studies, benchmarks, online and offline evaluation, best practices)
• Crowdsourcing (e.g. task assignment, worker reliability, optimization, trustworthiness, transparency, crowdsourcing in the era of large language models)
• Mining multi-modal content (e.g., natural language processing, speech recognition, computer vision, content understanding, knowledge extraction, knowledge representations)
• Data presentation (e.g., visualization, summarization, readability, VR, speech input/output)
• Fairness, Ethics, and Explainability in Information and Knowledge Management (e.g., fairness, accountability, ethics, explainability)
• Applications (e.g., urban systems, biomedical and health informatics, legal informatics, crisis informatics, computational social science, data-enabled discovery, social networks, education, business)
• Generative AI for Data and Knowledge Management (e.g., GenAI for structured and unstructured data processing, GenAI for data synthesis and simulation, GenAI for information summarization, content creation, and visualization)
• Resource Efficient Generative AI models for knowledge management (e.g., model compression, distributed learning, and leveraging edge computing to reduce computational overhead.)

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Paper Submissions
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Authors are invited to submit original, full-length research papers that are not previously published, accepted to be published, or being considered for publication in any other forum. Full-length papers should satisfy the standard requirements of top-tier international research conferences.

Manuscripts should be submitted to CIKM 2025 Easychair site in PDF format, using the 2-column ACM sigconf template, see https://www.acm.org/publications/proceedings-template. Full papers cannot exceed 9 pages, including an appendix, plus unlimited pages for the GenAI Usage Disclosure section and references (paper content is limited to 9 pages, that means that if you have an appendix, then it should be included within that page limit. It is also ok if you do not have an appendix and instead 9 pages of content). Rejected full papers will not be considered for publication as short papers. The review of manuscripts will be double-blind, and submissions not properly anonymized will be desk-rejected without review.

Papers that include text generated from a large-scale language model (LLM), such as ChatGPT, are prohibited unless this produced text is presented as a part of the paper’s experimental analysis. AI tools may be used to edit and polish authors’ work, such as using LLMs for light editing of their text (e.g., automate grammar checks, word autocorrect, and other editing of author-written text), but text “produced entirely” by generative/AI models is not allowed.

At least one author of each accepted paper must register to present the work on-site in Seoul, Korea as scheduled in the conference program.

The official publication date is when the proceedings are made available in the ACM Digital Library. This date may be up to two weeks before the first day of the conference. The official publication date affects the deadline for any patent filings related to published work.

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