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    Editorial note: Advances in visual analytics and mining visual data
    (Springer, 2018) Aljawarneh, Shadi A.; Bayat, Oğuz
    Multimedia Tools and Applications gratefully acknowledges the editorial work of the scholars listed below on the special issue entitled, BAdvances in Visual Analytics and Mining Visual Data.
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    IEEE access special section editorial: Machine learning designs, implementations and techniques
    (Ieee-Inst Electrical Electronics Engineers Inc, 2020) Aljawarneh, Shadi A.; Bayat, Oğuz; Lara, Juan A.; Schumaker, Robert P.
    Most modern machine learning research is devoted to improving the accuracy of prediction. However, less attention is paid to the deployment of the machine and deep learning systems, supervised/unsupervised techniques for mining healthcare data, and time series similarity and irregular temporal data analysis [item 1)–9) in the Appendix]. Most deployments are in the cloud, with abundant and scalable resources, and a free choice of computation platform. However, with the advent of intelligent physical devices—such as intelligent robots or self-driven cars—resources are more limited, and the latency may be strictly bounded [item 1)–9) in the Appendix].
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    Introduction to the special section on new trends in data mining, games engineering and database systems
    (Pergamon-Elsevier Science Ltd, 2018) Aljawarneh, Shadi A.; Bayat, Oğuz; Essaaidi, Mohamed
    Over the course of the last twenty years, research in data mining and databases have seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, electrical engineering, games engineering systems, genetics engineering, statistics, operations research, and information systems. Data mining supports a wide range of applications, from electrical power engineering,mining, medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business engineering applications in corporate planning, direct marketing, and credit scoring. In addition, database technologies have been developed such as XML and RDF databases to fit modern information systems applications. Research in information systems equally reflects this inter- and multi-disciplinary approach, thereby advocating a series of papers at the intersection of data mining, games engineering and database research. The actual data mining task is the automatic or semi-automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records, unusual records and dependencies. The Knowledge Discovery in Databases (KDD) process is commonly defined with the following stages: (1) Selection, (2) Pre-processing (3) Transformation, (4) Data Mining and (5) Interpretation/Evaluation.
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    Introduction to the special section on new trends in data mining, games engineering and database systems
    (Pergamon-Elsevier Science Ltd, 2018) Aljawarneh, Shadi A.; Bayat, Oguz; Essaaidi, Mohamed
    [No abstract available]