DMDMS 2018
Date: May 08, 2018 1:00 am – May 11, 2018 12:00 pm
Location: Porto, Portugal
2nd International Workshop on Data Mining for Decision Making Support (DMDMS 2018)
In Conjunction with the 9th International Conference on Ambient Systems, Networks and Technologies
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 Making Support (DMS) 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 (DM) 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. DM also helps to discover interesting business insights to help make business decisions that can influence cost efficiency and yet maintain a high quality of business management.
Scope
This workshop will provide a common platform for discussion of challenging issues and potential techniques in this emerging 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, 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
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2nd International Workshop on Data Mining for Decision Making Support (DMDMS 2018)
In Conjunction with the 9th International Conference on Ambient Systems, Networks and Technologies
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 Making Support (DMS) 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 (DM) 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. DM also helps to discover interesting business insights to help make business decisions that can influence cost efficiency and yet maintain a high quality of business management.
Scope
This workshop will provide a common platform for discussion of challenging issues and potential techniques in this emerging 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, 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