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Call for papers: Data mining for decision making support (DMDMS), May 23-26, 2016, Madrid, Spain

Paper Submission deadline: January 9, 2016

Decision making support systems (DMSS) are widely used to support business or organizational decision-making. They are used to inform decisions at all levels of an organization. Decision Support often needs to use and mine large amounts of data collected from multiple sources and, learn objectives or decision preferences from decision makers' responses.

Data mining has aided in several aspects of decision making.Data mining for decision making support (DMDMS) is an emerging field where researchers from both academia and industry have recognized the potential of its impact on improved decisions by discovering patterns and trends in large amounts of complex data generated by decision transactions. Data mining also helps to discover interesting business insights to help make business decisions that can influence cost efficiency and yet maintain a high quality of care.

Scope

This workshop will provide a common platform for discussion of challenging issues and potential techniques in this emergence field of data mining for decision support. It will also serve as a critical and essential forum for integrating various research challenges in this domain and promote collaboration among researchers from academia and industry to enhance the state-of-art and help define a clear path for future research in this emerging area. The workshop invites researchers and practitioners to submit original work on methodologies, models, algorithms, systems, tools, applications and case studies of DMDMS. Most importantly, the workshop will be a forum to discuss how to utilize advances from multiple disciplines for building DMDMS that can intelligently merge human knowledge and expertise with formal models to make better decisions.

Topics

The topics of interest for the workshop include, but are not limited to:


Knowledge management for DMS
Ontologies for DMS
Case-based reasoning for DMS
Business intelligence for DMS
Data mining for DMS
Optimization methods for DMS
Knowledge and resource discovery for DMS
Information and Knowledge Retrieval for DMS
Group, distributed, and collaborative DMS
Big Data Analytics and DMS
Case studies of DMDMS

Workshop Chairs

Abdelkader Adla, University of Oran 1, Algeria

Baghdad Atmani, University of Oran 1, Algeria

For Additional information consult: http://www.univ-oran1.dz/images/workshop/index.html



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