ICDM: International Conference on Data Mining



Past:   Proceedings on DBLP

Future:  Post a CFP for 2025 or later   |   Invite the Organizers Email


All CFPs on WikiCFP

Event When Where Deadline
ICDM 2024 IEEE International Conference on Data Mining
Dec 9, 2024 - Dec 12, 2024 Abu Dhabi, UAE Jul 1, 2024
ICDM 2023 International Conference on Data Mining
Dec 1, 2023 - Dec 4, 2023 Shanghai, China (hybrid) Jul 1, 2023
ICDM 2022 22nd IEEE International Conference on Data Mining
Nov 30, 2022 - Dec 3, 2022 Orlando, FL, USA Jun 10, 2022
ICDM 2021 21st IEEE International Conference on Data Mining
Dec 7, 2021 - Dec 10, 2021 Auckland, New Zealand Jun 11, 2021
ICDM 2020 20th IEEE International Conference on Data Mining
Nov 17, 2020 - Nov 20, 2020 Sorrento, Italy Jun 11, 2020
ICDM 2018 IEEE International Conference on Data Mining
Nov 17, 2018 - Nov 20, 2018 Singapore Jun 5, 2018
ICDM 2017 IEEE International Conference on Data Mining 2017
Nov 18, 2017 - Nov 21, 2017 NEW ORLEANS, USA Jun 5, 2017
ICDM 2016 The IEEE International Conference on Data Mining
Dec 12, 2016 - Dec 15, 2016 Barcelona, Spain Jun 17, 2016
ICDM 2014 IEEE International Conference on Data Mining
Dec 14, 2014 - Dec 17, 2014 Shenzhen, China Jun 24, 2014
ICDM 2013 IEEE International Conference on Data Mining
Dec 8, 2013 - Dec 11, 2013 Dallas, Texas, USA Jun 21, 2013
ICDM 2012 IEEE International Conference on Data Mining
Dec 10, 2012 - Dec 13, 2012 Brussels / Belgium Jun 18, 2012
ICDM 2010 The 10th IEEE International Conference on Data Mining
Dec 13, 2010 - Dec 17, 2010 Sydney, Australia Jul 2, 2010
ICDM 2009 The 2009 IEEE International Conference on Data Mining
Dec 6, 2009 - Dec 9, 2009 Miami, FLorida ,USA Jun 26, 2009
ICDM 2008 The 8th IEEE International Conference on Data Mining
Dec 15, 2008 - Dec 19, 2008 Pisa, Italy Jul 7, 2008

Present CFP : 2024

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 presentation of original research results, as well as exchange and dissemination of 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, and high-performance computing. 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.
Deep learning and statistical methods for data mining.
Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data.
Data mining systems and platforms, and their efficiency, scalability, security and privacy.
Data mining for modelling, visualization, personalization, and recommendation.
Data mining for cyber-physical systems and complex, time-evolving networks.
Applications of data mining in social sciences, physical sciences, engineering, life sciences, 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, which have not been published elsewhere and which 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 possible appendices. Submissions longer than 10 pages will be rejected without review. All submissions will be triple-blind reviewed by the Program Committee on the basis of technical quality, relevance to scope of the conference, originality, significance, and clarity. The following sections give further information for authors.
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.

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