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DSEA 2020 : The Fourth International Workshop on Data Science Engineering and its Applications

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Link: http://emergingtechnet.org/DSEA2020/
 
When Dec 14, 2020 - Dec 16, 2020
Where Paris, France
Submission Deadline Nov 5, 2020
Notification Due Nov 15, 2020
Final Version Due Dec 1, 2020
Categories    data science   data mining   edge and cloud   machine learning
 

Call For Papers

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 Fourth International Workshop for Data Science Engineering and Applications (DSEA 2020) 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.

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

Architecture, management and process for Data Science
Big Data Mining and Knowledge Management
Evaluation and Measurement in Data Science
Privacy and protection standards and policies for Data Science
Data Quality
Data science for the internet of things (IoT)
Management Issues of Social Network Big Data
Big Data Computing for Data science/li)
Social Network and Big Data Analytics
Open Source tools for Data Science and Big Data
Data Mining for Data science
High performance computing for data analytic
Mathematical Issues in Data Science and Applica

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