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SCDS 2017 : 3rd International Conference on Soft Computing in Data Science

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Link: https://aaec.uitm.edu.my/scds2017/index.php
 
When Nov 27, 2017 - Nov 28, 2017
Where Yogyakarta, Indonesia
Submission Deadline Jul 31, 2017
Notification Due Aug 25, 2017
Final Version Due Sep 15, 2017
Categories    big data analytics   deep learning   data mining   optimization algorithms
 

Call For Papers

______________________________________________
EXTENDED DEADLINE : 31st JULY 2017
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We welcome you to participate in The 3rd International Conference on Soft Computing in Data Science 2017 (SCDS 2017) which will be held in Yogyakarta (Hotel To Be Announced) from 27-28 November 2017. The theme of the conference is ‘Science in Analytics: Harnessing Data and Simplifying Solutions’. Data science can improve corporate decision-making and performance, personalize medicine and healthcare services and improve organizations efficiency and performance. Data Science is about learning from your data. Thus, with the advancement in computer technology huge amount of data can be stored and harnessed. Data science and analytics plays an important role in various disciplines including business, medical and health informatics, social sciences, manufacturing, economics, accounting and finance.

SCDS2017 aims to provide a platform for discussions on leading edge methods and also addressing challenges, problems and issues in data science and big analytics. The role of data science and big data analytics is significantly increasing in every field from business, engineering to life sciences and with advanced computer algorithms, solutions for complex real problems can be simplified. For the advancement of society in the 21st century, there is a need to transfer knowledge and technology to industrial applications to solve real-world problems. SCDS2017 have invited renowned international and local keynote speakers who are academia or practitioners to share their knowledge and experience in the area of machine learning in data science and analytics.

SCDS2017 aims to attract researchers who are actively engaged both in theoretical and practical aspects of Soft Computing in Data Science. The focus is theory and applications of Data Science and Big Data Analytics. Authors are invited to contribute to the conference by submitting articles in the following areas, but are not limited to the following topics:

• Big Data Analytics
• Big Data Technologies
• Decision Tree Learning
• Association Rule Learning
• Artificial Neural Networks
• Support Vector Machines
• Deep Learning
• Reinforcement Learning
• Clustering
• Bayesian models and methods
• Genetic algorithms
• Data Representation and Visualization
• Data Mining
• Fuzzy Logic
• Optimization Algorithms
• Graph/Network/Social Mining

Applications include but are not limited to the following areas:

• Business Analytics
• Customer Analytics
• Financial Analytics
• Bioinformatics
• Talent Analytics
• Information Analytics
• Marketing Analytics
• Operations Analytics
• Text and Sentiment analysis

Paper Submission

SCDS2017 accepts only high-quality papers for its conference proceedings, which are subject to a thorough & objective review process of at least 3 independent reviewers. Authors are invited to submit original unpublished manuscripts that demonstrate current research on one of the SCDS2017 topics of interest. All submissions will be handled electronically; detailed submission instructions will be provided on the conference homepage. The acceptance rate for SCDS2015 and SCDS2016 was 38% and 41% respectively.

Authors are invited to electronically submit original research contributions in English.
• The length of submitted manuscripts should not exceed 15 pages.
• Full papers: Minimum 10 pages and Maximum 15 pages.
• Over-length charges will apply for each extra page beyond 10 pages.

Publications

All accepted conference papers will be published in the proceedings with Springer. SCDS2015 and SCDS2016 proceedings were published in the Communications in Computer and Information Science series which is abstracted (indexed) by DBLP, EI, Scopus and it is submitted for the inclusion in ISI Proceedings.

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