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Computer Science and Data Mining
Submission Deadline: Oct. 25, 2019

This special issue currently is open for paper submission and guest editor application.

Join as Guest Editor Submit to Special Issue
Lead Guest Editor
Weiya Fan
Chongqing Normal University, Chongqing, China
Guest Editors
  • Tingting Li
    Chongqing Normal University, Chongqing, China
  • Yanlu Gong
    Chongqing Normal University, Chongqing, China
  • Li Zhu
    Chongqing Normal University, Chongqing, China
  • Maoyuan Ma
    Chongqing Normal University, Chongqing, China
  • Shanwen Yang
    Chongqing Normal University, Chongqing, China
Guidelines for Submission
Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.
Papers should be formatted according to the guidelines for authors (see: http://www.sciencepublishinggroup.com/journal/guideforauthors?journalid=134). By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at http://www.sciencepublishinggroup.com/login. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.
Published Papers
The special issue currently is open for paper submission. Potential authors are humbly requested to submit an electronic copy of their complete manuscript by clicking here.

Special Issue Flyer (PDF)

Please download to know all details of the
Special Issue

Introduction
The Special Issue are to (a) present the current state of the art of data mining and knowledge discovery through an ongoing series of reviews written by leading researchers, (b) capture the crucial interdisciplinary flavor of the field by including articles that address the key topics from the differing perspectives of data mining and knowledge discovery, including a variety of application areas in technology, business, healthcare, education, government and society and culture, (c) capture the rapid development of data mining and knowledge discovery through a systematic program of content updates, and (d) encourage active participation in this field by presenting its achievements and challenges in an accessible way to a broad audience. The Special Issue will be useful to upper-level undergraduate and postgraduate students, to teaching and research professors in academic programs, and to scientists and research managers in industry.
The techniques of CSDM are now being applied in many areas of business and government, such as banking and finance, market research, risk analysis, and counterterrorism. In the sciences, CSDM has become pervasive in such fields as bioinformatics, medical diagnosis, epidemiology, drug discovery, environmental modeling, and meteorological data analysis.

Aims and Scope:

  1. Computer Science
  2. Machine Learning
  3. Data Mining
  4. Artificial Intelligence
  5. Information Systems
  6. Multidisciplinary
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