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 2023 will take place between October 21-25, 2023 in Birmingham, UK.

Key Dates
All deadlines are at 11:59pm in the Anywhere on Earth timezone.
  • Full Papers Abstract Deadline: 26 May 2023

  • Full Papers Final Deadline: 2 June 2023

  • Papers Notifications: 4 August 2023

  • Camera Ready Deadline: 18 August 2023


Topics of Interest

We encourage submissions of high quality research papers on all topics in 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 and information acquisition and preprocessing (e.g., data crawling, IoT data, data quality, data privacy, mitigating biases, data wrangling)

  • Integration and aggregation (e.g., semantic processing, data provenance, data linkage, data fusion, knowledge graphs, data warehousing, 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, 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, understanding, 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., ad hoc and web search, facets and entities, question answering and dialogue systems, retrieval models, query processing, personalization, recommender and filtering systems)

  • Users and interfaces for information and data systems (e.g., user behavior analysis, user interface design, perception of biases, personalization, interactive information retrieval, interactive analysis, spoken interfaces)

  • Evaluation, performance studies, and benchmarks (e.g., online and offline evaluation, best practices)

  • Crowdsourcing (e.g. task assignment, worker reliability, optimization, trustworthiness, transparency, best practices)

  • Understanding multi-modal content (e.g., natural language processing, speech recognition, computer vision, content understanding, knowledge extraction, knowledge graphs, and knowledge representations)

  • Data presentation (e.g., visualization, summarization, readability, VR, speech input/output)

  • Applications (e.g., urban systems, biomedical and health informatics, legal informatics, crisis informatics, computational social science, data-enabled discovery, social media)


Paper Submissions

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 2023 Easychair site in PDF format, using the ACM sigconf template, see https://www.acm.org/publications/proceedings-template. Submissions should be in 2-column sigconf format. Full papers cannot exceed 9 pages, including appendix, plus unlimited references. Rejected full papers will not be considered for publication as short papers. Paper review 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 own text (e.g., automate grammar checks, word autocorrect, and other editing work), but text “produced entirely” by AI is not allowed. For CIKM 2023, we adhere to the principles and guidelines stated in the LLM policy @ ICML 2023.

At least one author of each accepted paper must register to present the work on-site in Birmingham as scheduled in the conference program, which may include both oral presentation and poster sessions. In case of traveling restrictions (COVID related or otherwise), an exception may be made to allow registered authors to present the work remotely.


Dual Submission Policy

It is not allowed to submit papers that are identical (or substantially similar) to versions that have been previously published, or accepted for publication, or that have been submitted in parallel to other conferences (or any venue with published proceedings). Such submissions violate our dual-submission policy. There are several exceptions to this rule:

  • Submission is permitted for papers presented or to be presented at conferences or workshops without proceedings, or with only abstracts published.

  • Submission is permitted for papers that have previously been made available as a technical report (or similar, e.g., in arXiv). In this case, the authors should not cite the report, so as to preserve anonymity.


ACM Policy Against Harassment

All authors and participants must adhere to the ACM Policy Against Harassment. For full details, please visit this site:

https://www.acm.org/about-acm/policy-against-harassment


PC Chair Contact Information


For more information, contact the appropriate PC chairs:


  • Full Paper Track Email: cikm2023-pc@easychair.org

  • Min Zhang, Tsinghua University, China

  • Mounia Lalmas, Spotify, UK

  • Rodrygo Santos, UFMG, Brazil


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