Special Issue "Data Stream Mining and Processing"
Deadline for manuscript submissions: closed (10 November 2018).
Interests: computer vision; artificial intelligence; machine learning; video data stream processing; neural networks; deep learning; IoT; pattern recognition; big data modelling
Interests: machine learning; computational intelligence; hybrid systems; wavelet neural networks; deep learning; prediction; clustering; classification; IoT; pattern recognition
Interests: data mining of complex data; objective clustering; bioinformatics; gene expression profile processing; gene regulatory network reconstruction and simulation
This Special Issue of Data is dedicated mainly to selected papers from the 2018 IEEE International Conference of Data Stream Mining and Processing held in Lviv, Ukraine, 21–25 August, 2018. Expanded versions of papers presented at the conference will be invited for submission to this special issue. However, it should be noted that this Special Issue is not limited conference materials. Original papers, which correspond to hereinbelow presented topics can also be published.
- Hybrid Systems of Computational Intelligence
Information processing systems which combine different approaches of Computational Intelligence, for example, artificial neural networks which are learnt by evolutionary algorithms, neuro-fuzzy systems, wavelet-neuro-fuzzy systems, neuro-neo-fuzzy systems, particle swarm algorithms, evolving systems, deep learning, etc.
- Machine Vision and Pattern Recognition
Video Streams that are fed from video cameras in an online mode under environment uncertainty and variability conditions.
- Dynamic Data Mining and Data Stream Mining
Data Mining problems (classification, clustering, prediction, identification, etc.) when information is fed in an online mode in the form of data streams.
- Big Data and Data Science Using Intelligent Approaches
Systems of Computational Intelligence (artificial neural networks, fuzzy reasoning systems, evolutionary algorithms) in the tasks of Big Data processing (high-dimensional data) where data are stored in VLDB or fed in an unlimited data stream. Natural Language Processing—machine learning using to get the semantic objects from natural language; the deep learning methods for natural language understanding.
Prof. Dr.Sc. Dmytro Peleshko
Prof. Dr.Sc. Olena Vynokurova
Associate prof. CSc. Sergii Babichev
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 papers will be 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.
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. Data is an international peer-reviewed open access monthly journal published by MDPI, indexed in the Emerging Sources Citation Index (ESCI) - Web of Science and Inspec (IET).
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 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.
Additional Information for Authors
Authors are obliged to expand their conference papers by adding 60% of the new research results, changing the title, and partly changing abstract and conclusions. Moreover, a reference to the paper from conference proceedings should be in the journal paper.
Technical Program Committee
List of the reviewers
Aizenberg I., D.Sc., Prof. (New York, USA), [email protected]
Antoshchuk S., D.Sc., Prof. (Odesa, Ukraine), [email protected]
Bidyuk P., D.Sc., Prof. (Kyiv, Ukraine), [email protected]
Bodyanskiy Ye., D.Sc., Prof., (Kharkiv, Ukraine), [email protected]
Boyun V., D.Sc., Prof. (Kyiv, Ukraine), [email protected]
Churyumov G., D.Sc., Prof., IEEE Senior Member (Kharkiv, Ukraine), [email protected]
Dyvak М., D.Sc., Prof. (Ternopil, Ukraine), [email protected]
Gozhiy O., D.Sc., Assoc. Prof. (Mykolayv, Ukraine), [email protected]
Hnatushenko V., D.Sc., Prof., IEEE Senior Member (Dnipro, Ukraine), [email protected]
Kharchenko V., D.Sc., Prof. (Kharkiv, Ukraine), [email protected]
Lytvynenko V., D.Sc., Prof. (Kherson, Ukraine), [email protected]
Lyubchik L., D.Sc., Prof., IEEE Member (Kharkiv, Ukraine), [email protected]
Mashkov V., D.Sc., Assoc. Prof. (Ústi nad Labem, Czech republic)
Mashtalir V., D.Sc., Prof. (Kharkiv, Ukraine), [email protected]
Petlenkov E., Ph.D., Prof. (Tallinn, Estonia), [email protected]
Rekik A., Ph.D. (Sfax, Tunisia), [email protected]
Romanyshyn Yu., D.Sc., Prof. (Lviv, Ukraine), [email protected]
Sachenko A., D.Sc., Prof. (Ternopil, Ukraine), [email protected]
Setlak G., D.Sc., Prof. (Rzeszów, Poland), [email protected]
Shelevytsky I., D.Sc., Prof. (Kryvyi Rih, Ukraine), [email protected]
Sokolovsky Ya., D.Sc., Prof. (Lviv, Ukraine), [email protected]
Stepashko V., D.Sc., Prof. (Kyiv, Ukraine), [email protected]
Štěpnička M., Ph.D., Assoc. Prof. (Ostrava, Czech Republic), [email protected]
Vassiljeva K., Ph.D., Assoc. Prof. (Tallinn, Estonia), [email protected]
Wójcik W., Dr. hab.inz. (Lublin, Poland)
Kulishova N., Ph.D., Assoc. Prof., (Kharkiv, Ukraine), [email protected]
Volkova V., Ph.D., Assoc. Prof., (Kyiv, Ukraine), [email protected]
Yatsymirskyy М., D.Sc., Prof. (Łódź, Poland), [email protected]
Alekseyev V., Ph.D., Assoc. Prof. (Lviv, Ukraine), Vladislav Alekseyev <[email protected]>
Dumin O., Ph.D., Assoc. Prof., IEEE Ukraine Section (Kharkiv) (Kharkiv, Ukraine), [email protected]
Panchenko T., Ph.D., Assoc. Prof., Member of the Board of Directors at ACM Ukrainian Chapter (Kyiv, Ukraine) [email protected]
Andrew Smith, Ph.D., (Dublin, Ireland) [email protected]
Bohdan Pavlyshenko, Ph.D., Assoc. Prof., (Lviv, Ukraine), bohdan [email protected]
Mike Hinchey, Ph.D., President, International Federation for Information Processing (IFIP); Professor of Software Engineering, University of Limerick; Emeritus Director, Lero-the Irish Software Research Centre; Chair, IEEE UK & Ireland section (Limerick, Ireland), [email protected]
Minho Jo, Ph.D., Chairman of IoT and Cognitive Networks Lab and Professor of Department of Computer Convergence Software at Korea University (Sejong Metro, South Korea), [email protected]
- Big Data
- Artificial Intelligence
- Data Mining
- Data Science
- Deep learning
- Machine Vision
- Pattern Recognition
- Computational Intelligence
- Hybrid Systems