Today, Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. It involves many domains, such as signal processing, probability models, machine learning, data mining, database, data engineering, pattern recognition, visualization, predictive analytic, data warehousing, data compression, computer programming, etc. High Performance Computing typically deals with smaller, highly structured data sets and huge amounts of computation.
Data Science has emerged to tackle the problem of creating processes and approaches to extracting knowledge or insights from gigantic, unstructured data sets. The International Workshop for Data Science Engineering and Applications (DSEA 2017) aims to provide a forum that brings together researchers, industry practitioners and domain experts for discussion and exchange of ideas on the latest theoretical developments in Data Science and Computing as well as on the best practices for a wide range of applications.
Researchers are encouraged to submit original research contributions in all major areas, which include, but not limited to:
Architecture, management and process for data science
Data science for the internet of things (IoT)
Big Data Computing
Data Mining for Data science
Cloud computing and service data analysis
Data warehouses, cloud architectures
Mathematical Issues in Data Science Big Data Issues and Applications
Large-scale databases
High performance computing for data analytic
Large scale optimization
Data-driven Scientific Research
Security, trust and risk in big data
Privacy and protection standards and policies
Data Quality
Evaluation and Measurement in Data Science
Big Data Mining and Knowledge Management
Case Study of Data Science
10月11日
2017
10月13日
2017
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