Cloud computing has become ubiquitous and is transforming the way computing works at scale. Cloud based data systems have evolved from basic infrastructure for data storage (under IaaS), to sophisticated platforms (under PaaS) that enable processing big and complex data. Such platforms often include data mining capabilities and machine learning models that enable numerous applications and services to run in the cloud. Several new cloud based machine learning platforms have emerged including Microsoft AzureML, Amazon ML framework, DataRobot, Dato, H2O and others and there is a rapidly growing applied data science community that is using such cloud platforms to conduct applied as well as theoretical advances.
The CLOUDMINE workshop aims to bring together researchers and practitioners working on cloud based data mining systems and applications. While the data mining community includes tracks and workshops to discuss research that implicitly leverages cloud based applications and scale, the CLOUDMINE workshop targets researchers who can discuss challenges faced by data mining systems and applications used for model building and deployments in the cloud.
The workshop will engage researchers in two broad sessions based on synergistic yet different topics:
- The first session will cover theoretical challenges and recent advances in data mining techniques and algorithms that improve performance of cloud based data mining platforms, and data intensive cloud based implementations of such algorithms. Examples include distributed data systems, or data mining algorithms for improved storage or data movement for cloud based architectures.
- The second session will cover interdisciplinary data mining applications and solutions in the cloud that enable technology systems in any domain to become cloud enabled in a way that makes the cloud technology indispensable. At a minimum, data mining in the cloud should improve the technology system far beyond the on premise version of the system, by leveraging the unique features of the cloud.
Both of the sessions will accept high-quality research papers that demonstrate how to transform cloud based research and technology, and redefine cloud landscape by using advanced data mining tools and techniques to push the frontiers of cloud computing.
Paper submissions are limited to a maximum of 8 pages in the IEEE 2-column following IEEE ICDM 2016 submission guidelines available here. Papers should be submitted in PDF format, electronically, to the CyberChair submission system.
All papers will be reviewed by the Program Committee based on technical quality, relevance to the workshop description, originality, significance, and clarity. All accepted workshop papers will be included in the IEEE ICDM 2016 Workshops Proceedings volume, and will also be included in the IEEE Xplore Digital Library.
- Vani Mandava, Microsoft Research, firstname.lastname@example.org
- David Carrera, Barcelona Supercomputing Center, email@example.com
- Dani Villatoro, Vodafone UK
- Jordi Nin, BBVA Data Analytics
- Josep Lluis Berral, BSC
- Muhammad Ahmad, Groupon
- Rania Khalaf, IBM Research
- Rodolfo Milito, Cisco
- Vanja Paunic, Microsoft