# CIKM — ACM International Conference on Information and Knowledge Management

- **Submission deadline**: 2026-05-16
- **Notification date**: 2026-08-07
- **Conference date**: 2026-11-07
- **Location**: Rome, Italy
- **Rankings**: CCF B · CORE A · QUALIS A1
- **Trackers**: 489
- **Attendees**: 92
- **Canonical page**: https://www.myhuiban.com/conference/143

## Acceptance history

| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| 2021 | 1251 | 271 | 21.7% |
| 2020 | 920 | 193 | 21% |
| 2019 | 1030 | 200 | 19.4% |
| 2018 | 862 | 147 | 17.1% |
| 2017 | 855 | 171 | 20% |
| 2016 | 701 | 160 | 22.8% |
| 2015 | 646 | 165 | 25.5% |
| 2014 | 838 | 175 | 20.9% |

## Call for papers

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: Data Acquisition and Processing: IoT data, data quality, data privacy, mitigating biases, data wrangling, data exploration, data preparation, valuation, and tradin Data Integration and Aggregation: semantic processing, data provenance, data linkage, data fusion, knowledge graphs, data warehousing, data lakes, privacy and security, modeling, information credibility, AI-generated content detection and provenance) Efficient Data Processing: serverless computing, data-intensive computing, database systems, indexing and compression, architectures, distributed data systems, dataspaces, customized hardware Special Data Processing: multilingual text, sequential, stream, time series, spatio-temporal, (knowledge) graph, multimedia, scientific, and social media data Analytics and Machine Learning: OLAP, data mining, machine learning and AI, scalable analysis algorithms, algorithmic biases, event detection and tracking, interpretability and explainability Foundation Models and Neural Information Processing: large language models, graph neural networks, domain adaptation, transfer learning, in-context learning, fine-tuning and alignment, network architectures, neural ranking, neural recommendation, and neural prediction Agentic AI for Information and Knowledge Tasks: tool use, planning, multi-agent systems, autonomous retrieval and decision-making, agentic workflows, orchestration of knowledge-intensive processes Information Access and Retrieval: retrieval-augmented generation (RAG), retrieval models, query processing, question answering and dialogue systems, open-ended question answering, conversational information seeking, generation of knowledge graphs from unstructured data, personalization, recommender systems, filtering systems Trustworthy and Responsible AI: fairness, accountability, ethics, explainability, safety, alignment, robustness, hallucination detection and mitigation, factuality and grounding, attribution, responsible deployment Users and Interfaces for Information Systems: user behavior analysis, user interface design, perception of biases, interactive information retrieval, interactive analysis, spoken interfaces, human-AI collaboration, co-pilot paradigms, human-in-the-loop systems Evaluation: performance studies, benchmarks, online and offline evaluation, best practices, evaluation of generative and LLM-based systems, human evaluation protocols, LLM-as-judge, reproducibility Crowdsourcing: task assignment, worker reliability, optimization, trustworthiness, transparency, crowdsourcing in the era of large language models Mining Multi-Modal Content: natural language processing, speech recognition, computer vision, content understanding, knowledge extraction, knowledge representations, multi-modal foundation models Data Presentation: visualization, summarization, readability, VR/AR, speech input/output Generative AI for Data and Knowledge Management: GenAI for structured and unstructured data processing, GenAI for data synthesis and simulation, GenAI for information summarization, content creation, and visualization, synthetic data generation, and quality Resource-Efficient AI: model compression, quantization, distillation, distributed learning, inference optimization, on-device models, leveraging edge computing to reduce computational overhead Applications: urban systems, biomedical and health informatics, legal informatics, crisis informatics, computational social science, data-enabled discovery, social networks, education, business

## Related conferences

- IC3K — International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management — https://www.myhuiban.com/conference/3176
- ICRA — International Conference on Robotics and Automation — https://www.myhuiban.com/conference/421
- IJCAI — International Joint Conference on Artificial Intelligence — https://www.myhuiban.com/conference/405
- ICASSP — International Conference on Acoustics, Speech and Signal Processing — https://www.myhuiban.com/conference/429
- PODS — ACM SIGMOD Conference on Principles of DB Systems — https://www.myhuiban.com/conference/138

## Related journals

- Expert Systems with Applications — https://www.myhuiban.com/journal/210
- Information Systems — https://www.myhuiban.com/journal/116
- Data & Knowledge Engineering — https://www.myhuiban.com/journal/109
- Information & Management — https://www.myhuiban.com/journal/126
- Information Technology and Management — https://www.myhuiban.com/journal/128

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Source: Conference Partner — https://www.myhuiban.com/conference/143 (rankings reproduced from CCF / ICORE / QUALIS; data cached up to 1 hour)