International Conference on Data Mining
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| International Conference on Data Mining | |
|---|---|
| Name | International Conference on Data Mining |
| Status | Active |
| Genre | Academic conference |
| Frequency | Annual |
| First | 1990s |
| Discipline | Computer science |
International Conference on Data Mining The International Conference on Data Mining is a recurring scholarly meeting focused on data mining, machine learning, pattern recognition, big data, and related computational methods. It attracts researchers from institutions such as Massachusetts Institute of Technology, Stanford University, Carnegie Mellon University, University of California, Berkeley, and University of Oxford, alongside industry groups like Google, Microsoft, IBM, Amazon (company), and Facebook. The conference forms part of a network of events linked to NeurIPS, ICML, KDD (conference), AAAI Conference on Artificial Intelligence, and SIGKDD.
History
The conference emerged during the 1990s amid parallel developments at Bell Labs, IBM Research, AT&T Bell Laboratories, Los Alamos National Laboratory, and Lawrence Berkeley National Laboratory. Early programs reflected methods from Bayesian statistics, decision trees, and neural networks, with contributors from University of Toronto, University of Cambridge, ETH Zurich, Princeton University, and Harvard University. Over successive decades the meeting expanded alongside milestones at DARPA, European Research Council, and National Science Foundation funding initiatives, and intersected with advances publicized at International Joint Conference on Artificial Intelligence, Conference on Computer Vision and Pattern Recognition, and ACM SIGMOD Conference.
Scope and Topics
Sessions encompass theoretical work and applications spanning bioinformatics collaborations with National Institutes of Health, genomics projects tied to Wellcome Trust, and astronomy pipelines such as those used by European Southern Observatory and NASA. Methodological areas include support vector machines research from Corinna Cortes-related groups, deep learning developments from labs linked to Yoshua Bengio, Geoffrey Hinton, and Yann LeCun, and ensemble learning approaches seen at Netflix Prize teams. Application domains reported include case studies from Siemens, General Electric, Toyota, Walmart, and initiatives with United Nations agencies and World Health Organization partnerships.
Organization and Governance
The conference is organized by committees comprising representatives from IEEE, ACM, Association for Computing Machinery, The Alan Turing Institute, Chinese Academy of Sciences, Indian Institute of Science, and regional societies such as European Association for Data Science affiliates. Steering committees often include academics affiliated with University of Washington, University of Illinois Urbana–Champaign, Tsinghua University, Peking University, and McGill University. Program chairs coordinate peer review using platforms similar to those employed by Journal of Machine Learning Research editorial boards and arXiv preprint moderators.
Conferences and Proceedings
Proceedings are published in series associated with Springer, Elsevier, IEEE Xplore, and occasionally ACM Digital Library, indexed alongside works presented at SIGGRAPH and CHI Conference on Human Factors in Computing Systems. Selected proceedings have been hosted in cities including Boston, San Francisco, London, Beijing, Tokyo, Paris, Singapore, and Melbourne. Special workshop tracks have been co-located with events such as Workshop on Mining and Learning with Graphs, International Workshop on Big Data Analytics, and meetings organized by European Conference on Machine Learning.
Keynotes and Notable Papers
Keynote speakers have included prominent figures from Google DeepMind, OpenAI, Microsoft Research, Facebook AI Research, and influential academics associated with Stanford University School of Engineering, MIT Computer Science and Artificial Intelligence Laboratory, and Berkeley AI Research. Notable papers presented at the conference later influenced work referenced alongside breakthroughs like the ImageNet project, the AlexNet architecture, and influential publications in IEEE Transactions on Pattern Analysis and Machine Intelligence and Communications of the ACM.
Awards and Recognition
The conference confers awards analogous to those granted by ACM SIGKDD and IEEE. Typical honors include Best Paper, Best Student Paper, and Distinguished Service awards, sometimes mirrored by prizes affiliated with Turing Award-level recognition ceremonies and sponsored by corporations such as Intel, NVIDIA, Oracle Corporation, and SAP SE.
Participation and Attendance
Participants range from graduate students and postdoctoral researchers from Columbia University, Yale University, University of Michigan, and University of Toronto to senior scientists from Bell Labs, Facebook, Amazon Web Services, and NVIDIA. Attendees often present posters, demos, and tutorials, and engage with panels that include representatives from World Bank, European Commission, United States Department of Energy, and nonprofit groups such as The Alan Turing Institute.