Discovery Science 2016
- https://www.uniba.it/it/ricerca/dipartimenti/informatica/notizie-eventi/eventi/discovery-science-2016
- Discovery Science 2016
- 2016-10-19T09:00:00+02:00
- 2016-10-21T21:00:00+02:00
- The 19th International Conference on Discovery Science (DS 2016) provides an open forum for intensive discussions and exchange of new ideas among researchers working in the area of Discovery Science. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains.
- Quando dal 19/10/2016 09:00 al 21/10/2016 21:00 (Europe/Berlin / UTC200)
- Dove Bari, Italy
- Contatti Michelangelo Ceci
- Telefono +390805442285
- Sito web Visita il sito
-
Aggiungi l'evento al calendario
iCal
We welcome papers that focus on the analysis of different types of massive and complex data, including structured, spatio-temporal and network data. We particularly welcome papers addressing applications. Finally, we would like to encourage contributions from the areas of computational scientific discovery, mining scientific data, computational creativity and discovery informatics.
DS-2016 will be co-located with ALT-2016, the 27th International Conference on Algorithmic Learning Theory. The two conferences will be held in parallel, and will share their invited talks.
Traditionally the proceedings of DS series appear in the Lecture Notes in Artificial Intelligence Series by Springer-Verlag. In addition a special issue on Discovery Science is planned in a prestigious journal.
Important Dates:
Full paper submission: 21 May 2016
Author notification: 28 June 2016
Camera-ready papers due: 21 July 2016
Conference: 19-21 October 2016
Submissions
We invite submissions of research papers addressing all aspects of discovery science. We particularly welcome contributions that discuss the application of data analysis, data mining and other support techniques for scientific discovery including, but not limited to, biomedical, astronomical and other physics domains. Applications to massive, heterogeneous, continuous or imprecise data sets are of particular interests.
Papers may contain up to fifteen (15) pages and must be formatted according to the layout supplied by Springer-Verlag for the Lecture Notes in Computer Science series. The Program Committee reserves the right to offer acceptance as Short Papers (8 pages in the Proceedings) to some submission. Submitted papers may not have appeared in or be under consideration for another workshop, conference or a journal, nor may they be under review or submitted to another forum during the DS 2016 review process.
Submission Topics
Possible topics include, but are not limited to:
Knowledge discovery, machine learning and statistical methods
Ubiquitous Knowledge Discovery
Data Streams, Evolving Data and Models
Change Detection and Model Maintenance
Active Knowledge Discovery
Learning from Text and web mining
Information extraction from scientific literature
Knowledge discovery from heterogeneous, unstructured and multimedia data
Knowledge discovery in network and link data
Knowledge discovery in social networks
Data and knowledge visualization
Spatial/Temporal Data
Mining graphs and structured data
Planning to Learn
Knowledge Transfer
Computational Creativity
Human-machine interaction for knowledge discovery and management
Biomedical knowledge discovery, analysis of micro-array and gene deletion data
Machine Learning for High-Performance Computing, Grid and Cloud Computing
Applications of the above techniques to natural or social sciences.
General Chair ALT/DS 2016
Donato Malerba – University of Bari A. Moro
PC Chairs DS 2016:
Michelangelo Ceci – University of Bari A. Moro
Toon Calders – Université Libre de Bruxelles, Belgium