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Applied Data Analytics

This special issue belongs to the section “E: Applied Mathematics“.

Special Issue Information

Dear Colleagues,

In recent years, we have seen the proliferation of new data analytics methods and approaches. These developments have happened under the labels of machine learning, data mining, deep learning, and smart X (where X can stand for any domain of application, such as smart cities, and smart energy).

However, a road from generic methods to practical applications is not always straightforward. Typical problems include incomplete or dirty data, too small or biased data, a lack of reproducible experiments, missing code for the whole or parts of the method, unclear parameter or hyper parameter values, etc.

The aim of this Special Issue is to provide a forum for applied analytics researchers to present their original contributions describing their experience and approaches to the aforementioned or similar problems in real-life applications on data analytics. Improvements and modifications to the existing methods are also of interest.

Submissions should be original and unpublished. Extended versions of conference publications will be considered if they contain at least 50% new content.

Prof. Dr. Tomasz Wiktorski
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. 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 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Data analysis
  • Data science
  • Big data
  • Algorithms
  • Applied data analytics
  • Machine learning
  • Data mining.

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Mathematics - ISSN 2227-7390