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Machine Learning for Data Science and Analytics

Submission Deadline: 30 March 2020

Special Issue Editors 
Special Issue Information
Manuscript Submission Information
Published Papers

Special Issue Editors

Dr. V. Vinoth Kumar
Associate Professor, Department of Computer Science and Engineering, MVJ College of Engineering, Bangalore-67, India

Dr. David Asirvatham
Head for the School of Computing and IT, Taylor’s University, Malaysia

Dr. Biplab Sikdar
Department of ECE, National University of Singapore, Singapore- 117583 , Singapore

Special Issue Information

Dear Colleagues,

Machine learning is concerned with design and development of algorithms to understand the nature of underlying data and evolve behaviors based on empirical data. Algorithms designed by applying machine learning principles and techniques can easily adapt to new situations, scenarios and circumstances and are also capable of detecting and extrapolating patterns. Spam identification, Credit card fraud, Predicting customers behavior based on past customer data patterns, Minimizing use of resources by achieving optimization, Disease prediction and classification, Knowledge extraction from video, text, image and Bio-informatics data, Identifying disability patterns, Stock market and financial trend analysis, Customer segmentation are some of examples where machine learning is applicable. Another important objective of machine learning is to make applications being developed using ML algorithms to be able to self-generalize from limited data (or) datasets available.

The topics of interest includes, but are not limited to:
  • Improving software and hardware performance
  • Data and web mining
  • Machine Learning for data science
  • Intelligent and knowledge based system
  • Artificial Intelligence Techniques on Software Engineering
  • Natural language processing
  • Deep Learning
  • Big Data analysis frameworks to traffic monitoring and analysis
  • Internet of Things
  • Fuzzy set theory, fuzzy control and system
  • Networking and information security
  • Neural networks
  • Cloud computing
  • Data consistency
  • Acceleration for new ML algorithms
  • Survey and tutorial studies of ML acceleration

Dr. V. Vinoth Kumar
Dr. David Asirvatham
Dr. Biplab Sikdar
Guest Editors
Manuscript Submission Information
Authors can submit their manuscripts through online submission system. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to guest editors for perusal first.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere. All manuscripts are thoroughly refereed through a blind peer-review process. A guide for authors and other relevant information for submission of manuscripts are available on the Author Submission Guide page.
The regular Publication Fee in IJMLC is 350 USD, however, the authors who would like to submit for this issue will have a special reduction (50 USD), which means the article processing charge is 300 USD. Submitted papers should be well formatted and use good English. 

Published Papers

This special issue is now open for submission.

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net

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