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Data Mining and Machine Learning Applications
Submission DeadlineJan. 10, 2020

Submission Guidelines: http://www.sciencepublishinggroup.com/home/submission

Lead Guest Editor
Department of Software Engineering, The World Islamic Sciences and Education, Amman, Jordan
Guest Editors
  • Ahmed Otoom
    Social Security Funds, Amman, Jordan
  • Alumnus with Department of Electrical Engineering, University of Bridgeport, Bridgeport, Connecticut, USA
  • University of Dallas, Irving, Texas, USA
  • Abdallah Gharib
    University of Malaysia, Sarawak, Malaysia
  • Raed Alazaidah
    School of Computing, Northern University of Malaysia, Sintok, Kedah, Malaysia
  • Mohd Saifuzzaman
    Daffodil International University, Dhaka, Bangladesh
  • Anitha J
    Department of IT, Sri Ramakrishna Engineering College, Coimbatore, India
  • Lawrance R
    Department of Computer Applications, Ayya Nadar Janaki Ammal College, Sivkasi, TamilNadu, India
  • Santhosh Kumar
    GMR Institute of Technology, Rajam, India
  • Indranath Chatterjee
    JK Lakshmipa University, Jaipur, Rajasthan, India
Introduction
With the existence of gigantic data daily, the business strives to extract interesting patterns and take proactive decisions. The application of data mining and machine learning can gain success in the field of business as well as in the technical fields. In the last years, the applications over customers and their behaviors have increased dramatically as a way of driving forces to enhance business process and marketing strategies. Therefore, such applications provide business with intelligent capabilities for interpretation and decision-making processes for gaining profit of the business organization. Moreover, data mining and machine learning community have been applied in technical fields. It has been applied in software engineering in requirements engineering, program comprehension, maintenance, and software components analysis. Data mining and machine learning applications have also proven a useful tool in cybersecurity solutions for detecting vulnerabilities and proactively preventing attacks.
The goal of this special issue is to cover a variety of topics and issues related to data mining applications. The special issue also welcomes manuscripts in theories and algorithms of data mining. Each manuscript will be reviewed by academics and practitioners who have worked in similar problem areas. The targeted readerships are technical and academic, as well as professionals in the domain.
Aims and Scope:
  1. Applications of Data mining and Machine Learning
  2. Data Mining Process
  3. Data Transformations
  4. Data Analysis and Interpretations
  5. Pattern Recognition and Association Analysis
  6. Data Warehousing
  7. Image Processing
  8. Information Retrieval
  9. Risk Management Applications
  10. Artificial Intelligence Applications
  11. Software Engineering Applications
  12. Cybersecurity Applications
  13. Deep Learning
  14. Empirical Case studies
Guidelines for Submission
Manuscripts should be formatted according to the guidelines for authors
(see: http://www.sciencepublishinggroup.com/journal/guideforauthors?journalid=603).

Please download the template to format your manuscript.

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