Call for Papers (PDF)
Aims and Scope
The IEEE International Conference on Data Mining (ICDM) has established itself as the world’s premier research conference in data mining. It provides an international forum for sharing original research results, as well as for exchanging and disseminating innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, and applications. ICDM draws researchers, application developers, and practitioners from a wide range of data mining-related areas, such as big data, deep learning, pattern recognition, statistical and machine learning, databases, data warehousing, data visualization, knowledge-based systems, high-performance computing, and large models. By promoting novel, high-quality research findings and innovative solutions to challenging data mining problems, the conference seeks to advance the state of the art in data mining.
Topics of Interest
Topics of interest include, but are not limited to:
* Foundations, algorithms, models, and theory of data mining, including big data mining.
* Machine learning, deep learning, and statistical methods for big data.
* Mining heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data
* Data mining systems and platforms for analyzing big data, including methods for parallel and distributed data mining, federated learning, and their efficiency, scalability, security, and privacy
* Data mining for modeling, visualization, personalization, and recommendation
* Data mining for cyber-physical systems and complex, time-evolving networks
* Data mining with large language models
* Novel applications of data mining in data science, including big data analysis in social sciences, physical sciences, engineering, life sciences, climate science, web, marketing, finance, precision medicine, health informatics, and other domains
We particularly encourage submissions in emerging topics of high importance, such as ethical data analytics, automated data analytics, data-driven reasoning, interpretable modeling, modeling with evolving environments, multi-modal data mining, and heterogeneous data integration and mining.
Submission Guidelines
Authors are invited to submit original papers that have not been published elsewhere and are not currently under consideration for another journal, conference, or workshop.
Paper submissions should be limited to a maximum of ten (10) pages in the IEEE 2-column format (https://www.ieee.org/conferences/publishing/templates.html), including the bibliography and any appendices. Submissions longer than 10 pages will be rejected without review. All submissions will be triple-blind reviewed by the Program Committee based on technical quality, relevance to the scope of the conference, originality, significance, and clarity. The following sections provide further information for authors.
Manuscripts must be submitted electronically through the online submission system: https://www.wi-lab.com/cyberchair/2025/icdm25/scripts/submit.php?subarea=DM. Email submissions are not accepted.
Important Dates
- Full paper submissions: June 6, 2025
- Notifications to authors: August 25, 2025
**All submission deadlines are end-of-day in the Anywhere on Earth (AoE) time zone**
Triple-blind submission guidelines
Since 2011, ICDM has imposed a triple-blind submission and review policy for all submissions. Authors must hence not use identifying information in the text of the paper and bibliographies must be referenced to preserve anonymity. Any papers available on the Web (including arXiv) no longer qualify for ICDM submissions, as their author information is already public.
What is triple-blind reviewing? The traditional blind paper submission hides the referee names from the authors, and the double-blind paper submission also hides the author names from the referees. The triple-blind reviewing further hides the referee names among referees during paper discussions before their acceptance decisions. The names of authors and referees remain known only to the PC Co-Chairs, and the author names are disclosed only after the ranking and acceptance of submissions are finalized. It is imperative that all authors of ICDM submissions conceal their identity and affiliation information in their paper submissions. It does not suffice to simply remove the author names and affiliations from the first page, but also in the content of each paper submission.
Authors must thoroughly anonymize their submissions:
Replace author and institution details in the template with “Anonymous.”
Refer to prior work in the third person. For example: Instead of “We extend our earlier work on clustering (Smith, 2005),” write “This work extends Smith’s earlier work (Smith, 2005) on clustering.”
Exclude references to funding sources, acknowledgments, and auxiliary information that could reveal author identities.
Make statements about well-known or unique systems in a way that does not identify the authors.
Name submitted files carefully to avoid compromising anonymity (e.g., use "ANewApproachToClustering.pdf" instead of "Smith.pdf").
Reproducibility guidelines
Authors must complete a reproducibility checklist at the time of paper submission (the questions in PDF format) [https://www.cs.mcgill.ca/~jpineau/ReproducibilityChecklist-v2.0.pdf]. Authors are strongly recommended to start thinking about these questions already when writing the paper and to fill in the questionnaire well in time before the submission deadline. These responses will become part of each paper submission and will be shared with the area chairs and/or reviewers to help them in the evaluation process. Authors are encouraged to include in their papers all technical details (proofs, descriptions of assumptions, algorithm pseudocode) as well as information about each reproducibility criterion, as appropriate.
Reviewers will assess the reproducibility of the reported results, which will influence final decisions about each paper.
Best Paper Awards
Awards will be conferred at the conference to the authors of the best paper and the best student paper. A selected number of best papers will be invited for possible inclusion, in an expanded and revised form, in the Knowledge and Information Systems journal (http://kais.bigke.org/) published by Springer.
Attendance
ICDM is a premier forum for presenting and discussing current research in data mining. At least one author of each accepted paper must complete the conference registration and present the paper at the conference for it to be included in the proceedings and program.
Contact
For queries regarding ICDM 2025, please contact icdm2025chairs@gmail.com.