Data science - analytics and applications

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This volume presents the proceedings of the Second International Data Science Conference (iDSC2019), organized by Salzburg University of Applied Sciences, Austria. The conference united researchers, scientists, and business experts to explore agile approaches in data science, encompassing machine learning, artificial intelligence, data mining, and visualization. The collection includes case studies and theoretical papers that advance the field. Full-length scientific-track papers on Data Analytics are categorized into Complexity, NLP and Semantics, Modelling, and Comprehensibility. Real-world applications featured include investigations into insider trading via hypernetworks, a data-driven approach to detecting autism spectrum disorder, and sentiment analysis of Twitter posts. Theoretical contributions address topics such as Optimal Regression Tree Models through Mixed Integer Programming, Chance Influence in datasets with numerous features, and the use of Adversarial Networks for image augmentation. Additionally, five shorter student-track papers cover subjects like state-of-the-art deep learning methods for neural machine translation and a smart recommendation system for HMI/SCADA platforms. This compilation offers researchers and practitioners a comprehensive overview of current advancements in data science, fostering further study and application development.