The International Conference on Data Mining (ICDM) is thrilled to announce its call for papers for ICDM 2025! This prestigious conference, a cornerstone event for the data mining community, invites researchers, practitioners, and students to submit their cutting-edge work on all aspects of data mining and related fields. ICDM 2025 promises to be a pivotal gathering, showcasing groundbreaking advancements and fostering insightful discussions that will shape the future of data science.
Key Themes and Topics
ICDM 2025 welcomes submissions addressing a broad spectrum of data mining topics, including but not limited to:
Foundational Data Mining Techniques:
- Novel algorithms and techniques: Developments in areas like classification, clustering, regression, association rule mining, and anomaly detection. Submissions focusing on efficiency, scalability, and explainability are highly encouraged.
- Data preprocessing and feature engineering: Innovative methods for handling missing data, noisy data, and high-dimensional data. Focus on techniques that improve model performance and interpretability.
- Dimensionality reduction and feature selection: Submissions exploring advanced techniques for reducing data complexity while preserving crucial information are welcome.
Emerging Trends and Applications:
- Explainable AI (XAI) and trustworthy AI: Research on methods to enhance the transparency and interpretability of data mining models. Submissions focusing on fairness, accountability, and bias mitigation are particularly encouraged.
- Big Data and distributed data mining: Scalable algorithms and architectures for processing and analyzing massive datasets. Exploration of novel approaches to handle distributed and heterogeneous data sources is welcome.
- Deep learning for data mining: Innovative applications of deep learning techniques to various data mining problems, including image analysis, natural language processing, and time series analysis.
- Data mining for specific domains: Submissions focusing on applications in healthcare, finance, cybersecurity, social networks, and other relevant domains are strongly encouraged. We particularly welcome interdisciplinary work that tackles real-world challenges.
- Privacy-preserving data mining: Techniques for analyzing data while protecting sensitive information. Research on differential privacy, federated learning, and homomorphic encryption is highly valued.
Methodological Advancements:
- Uncertainty quantification and robustness: Methods for assessing the uncertainty and robustness of data mining models. Submissions addressing model validation and error analysis are welcome.
- Reinforcement learning for data mining: Applications of reinforcement learning techniques to improve the efficiency and effectiveness of data mining processes.
- Meta-learning and automated machine learning (AutoML): Research on automating the process of selecting, tuning, and deploying data mining models.
Submission Guidelines
Detailed submission guidelines, including deadlines and formatting requirements, will be available on the official ICDM 2025 website (link to be announced). We encourage prospective authors to regularly check the website for updates.
Important Dates
- Abstract Submission Deadline: [Date to be announced]
- Full Paper Submission Deadline: [Date to be announced]
- Notification of Acceptance: [Date to be announced]
- Camera-Ready Paper Deadline: [Date to be announced]
- Conference Dates: [Date to be announced]
Contact Information
For any inquiries regarding ICDM 2025, please contact the conference organizers at [Email address to be announced].
We look forward to receiving your high-quality submissions and welcoming you to ICDM 2025! Let's collaborate to advance the field of data mining and its transformative impact on society.
