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SDM 2019 : SIAM International Conference on Data Mining | |||||||||
Link: https://www.siam.org/conferences/CM/Main/sdm19 | |||||||||
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Call For Papers | |||||||||
Data mining is the computational process for discovering valuable knowledge from data – the core of modern Data Science. It has enormous applications in numerous fields, including science, engineering, healthcare, business, and medicine. Typical datasets in these fields are large, complex, and often noisy. Extracting knowledge from these datasets requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms. These techniques in turn require implementations on high performance computational infrastructure that are carefully tuned for performance. Powerful visualization technologies along with effective user interfaces are also essential to make data mining tools appealing to researchers, analysts, data scientists and application developers from different disciplines, as well as usable by stakeholders.
SDM has established itself as a leading conference in the field of data mining and provides a venue for researchers who are addressing these problems to present their work in a peer-reviewed forum. SDM emphasizes principled methods with solid mathematical foundation, is known for its high-quality and high-impact technical papers, and offers a strong workshop and tutorial program (which are included in the conference registration). The proceedings of the conference are published in archival form, and are also made available on the SIAM web site. Included Themes Methods and Algorithms: ----------------------- Anomaly & Outlier Detection Big Data & Large-Scale Systems Classification & Semi-Supervised Learning Clustering & Unsupervised Learning Data Cleaning & Integration Deep Learning & Representation Learning Frequent Pattern Mining Feature Extraction, Selection and Dimensionality Reduction Mining Data Streams Mining Graphs & Complex Data Mining on Emerging Architectures & Data Clouds Mining Semi-Structured Data Mining Spatial & Temporal Data Mining Text, Web & Social Media Online Algorithms Optimization Methods Parallel and Distributed Methods Probabilistic & Statistical Methods Scalable & High-Performance Mining Other Novel Methods Applications: ------------- Astronomy & Astrophysics Automation & Process Control Climate / Ecological / Environmental Science Customer Relationship Management Data Science Drug Discovery Finance Genomics & Bioinformatics Healthcare Management High Energy Physics Intelligence Analysis Internet of Things Intrusion & Fraud detection Logistics Management Recommendation Risk Management Social Network Analysis Supply Chain Management Other Emerging Applications Human Factors and Social Issues: -------------------------------- Ethics of Data Mining Intellectual Ownership Interestingness & Relevance Privacy and Fairness Models Privacy Preserving Data Mining Risk Analysis and Risk Management Transparency and Algorithmic Bias User Interfaces and Visual Analytics Other Human and Social Issues |
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