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

Paris, France
Event Date: Dec 14, 2020 - Dec 16, 2020
Submission Deadline: Oct 25, 2020
Notification of Acceptance: Nov 15, 2020
Camera Ready Version Due : Dec 01, 2020

About

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.

Call For Paper

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 Applications
  • Cloud Computing for Big Data and Social Networks
  • Data Science and Big Data for the Internet of Things
  • Data Science and Big Data Management for Large-scale databases
  • Data Science and Big Data for Decision Making
  • Visualization tools for Data Science and Big Data
  • Data-driven Scientific Research
  • Data warehouses and cloud computing support for Data Science

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