Applications (DSEA 2020)*
*http://emergingtechnet.org/DSEA2020/*
<http://emergingtechnet.org/DSEA2020/>
*In conjunction with **The Sixth International Conference on Social
Networks Analysis, Management and Security(SNAMS-2020)*
<http://emergingtechnet.org/SNAMS2020/index.php>
* Paris, France. December 14-16, 2020.*
*DSEA 2020 CFP*
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*
*Submissions Guidelines and Proceedings*
Manuscripts should be prepared in 10-point font using the IEEE 8.5" x 11"
two-column format (IEEE Templates
<https://www.ieee.org/conferences_events/conferences/publishing/templates.html>).
All papers should be in PDF format, and submitted electronically at Paper
Submission Link. A full paper must not exceed the stated length (including
all figures, tables and references). Submitted papers must present original
unpublished research that is not currently under review for any other
conference or journal. Papers not following these guidelines may be
rejected without review. Also submissions received after the due date,
exceeding length limit, or not appropriately structured may also not be
considered. Authors may contact the Program Chair for further information
or clarification.
All submissions are peer-reviewed by at least three reviewers. Accepted
papers will appear in the SNAMS Proceeding and to be submitted to IEEE
Xplore for inclusion. The proceedings are also submitted for indexing to EI
(Compendex), Scopus and other indexing services like DBLP.
Submitted papers must include original work, and must not be under
consideration for another conference or journal. Submission of regular
papers must not exceed 8 pages and must follow the IEEE paper format.
Please include up to 7 keywords, complete postal and e-mail address, and
fax and phone numbers of the corresponding author. Authors of accepted
papers are expected to present their work at the conference. Submitted
papers that are deemed of good quality but that could not be accepted as
regular papers will be accepted as short papers. Length of short papers
*Important Dates*
Submission Date: 5 November, 2020 (Final and Firm)
Notification to Authors: 15 November, 2020
Camera Ready Submission: 1 December, 2020
*Journal Special Issues*
Selected papers from the presented papers will be invited to submit an
extended version to number of journals. Papers will be selected based on
their reviewers' scores and appropriateness to the Journal's theme. All
extended versions will undergo reviews and must represent original
unpublished research work. Further details will be made available at a
later stage.
Please send any inquiry to the Emerging Tech. Network Team at:
emergingtechnetwork@gmail.com
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