The 20th International Conference on Discovery Science (DS 2017) is an open forum for intensive discussion and exchange of new ideas between the working in the scientific field. The scope of the Conference includes the development and analysis of the techniques of data mining, data mining, excellent data analysis, and its application in several fields of science.
We welcome the research that focuses on the different types of massive and complex data, including structured, space and data networks. We particularly welcome the role of the annexes. Finally, we would like to call for contributions in the areas of computational research, data mining, computer science and informatics discovery.
In general, the DS series routines appear in the lecture notes on a series of artificial intelligence, Springer-Verlag. In addition, a special "Discovery science" issue is planned on the training log computer. DS-2017 will be in conjunction with ALT-2017, the 28th International Conference on Learning theory. Both conferences will be held in parallel and will exchange your guest conversations.
Thanks to the careful indexing of the world's most important literature, the scientific website has become a standard for research and detection analysis. The Science web site combines publications and studies with quotes and indexing to control curable databases covering all disciplines. The Science web site is a unifying search tool that allows users to receive, analyze, and distribute information in a timely manner to a database.
Did you know that?
Indexing quotes, the foundation of the scientific web, is also the basis of the Google Pagerank search algorithm. 100% of the total number of 100 universities worldwide use the Science network. The scientific data network is used in 231 countries/regions with an average of more than 800 000 surveys per day.
We invite you to search for all aspects of discovery science. We note that data analysis and other methods of support for scientific research, including, but not limited to, biomedical, astronomical and other physical domains. Of particular interest are requests for massive, heterogeneous, continuous, or inaccurate data sets. Possible topics include, but are not limited to:
Knowledge discovery, learning about machines and statistical methods
Knowledge everywhere
Data flows, data evolution, and patterns
To change the definition and maintenance of models
Discovery of active knowledge
Learn text and web development
Extracting information from the scientific literature
Discover the knowledge of heterogeneous, unstructured, and multimedia data
Knowledge discovery in network data and links
Discovery of knowledge in social networks
Visualizing and knowing your data
Spatial / Temporal data
Data mining diagrams and structured data
Planning for study
Transfer of knowledge
Computational creativity
Communication between man and computer to discover and manage knowledge
Biomedical knowledge detection, microarray analysis and Gene elimination data
Learning computer for high-performance computing, grids, and cloud computing
Applying the methods described above to natural or social sciences
The program committee reserves the right to propose the adoption of a short role (8 pages in the process) for some presentations. The documents submitted to another workshop, conference or journal, nor could they be considered or submitted to another forum during the DS 2017 revision process.
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