ISSN: 2308-4464
ISBN: 978-1-61208-816-7

• Registered: with the Library of Congress of the United States of America (ISSN)
• Hosted: by Technische Informationsbibliothek (TIB) - German National Library of Science and Technology (Open Access)
• Gold open access: in ThinkMind Digital Library

DATA ANALYTICS 2020 is colocated with the following events as part of NexTech 2020 Congress:

• UBICOMM 2020, The Fourteenth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies
• ADVCOMP 2020, The Fourteenth International Conference on Advanced Engineering Computing and Applications in Sciences
• SEMAPRO 2020, The Fourteenth International Conference on Advances in Semantic Processing
• AMBIENT 2020, The Tenth International Conference on Ambient Computing, Applications, Services and Technologies
• EMERGING 2020, The Twelfth International Conference on Emerging Networks and Systems Intelligence
• DATA ANALYTICS 2020, The Ninth International Conference on Data Analytics
• GLOBAL HEALTH 2020, The Ninth International Conference on Global Health Challenges
• CYBER 2020, The Fifth International Conference on Cyber-Technologies and Cyber-Systems

DATA ANALYTICS 2020 Steering Committee

		Wolfram Wöß Institute for Application Oriented Knowledge Processing | Johannes Kepler University, Linz Austria			Kerstin Lemke-Rust Hochschule Bonn-Rhein-Sieg Germany
		George Tambouratzis Institute for Language and Speech Processing, Athena R.C. Greece			Les Sztandera Thomas Jefferson University USA
		Ivana Semanjski Ghent University Belgium

DATA ANALYTICS 2020 conference tracks:

Fundamentals for data analytics

Tools, frameworks and mechanisms for data analytics; Open API for data analytics; In-database analytics; Pre-built analytics (pattern, time-series, clustering, graph, statistical analysis, etc.); Analytics visualization; Multi-modal support for data analytics; Google/FaceBook/Twitter/etc. analytics; High-performance data analytics

Advanced topics in Deep/Machine learning

Distributed and parallel learning algorithms; Image and video coding; Deep learning and Internet of Things; Deep learning and Big data; Data preparation, feature selection, and feature extraction; Error resilient transmission of multimedia data; 3D video coding and analysis; Depth map applications; Machine learning programming models and abstractions; Programming languages for machine learning; Visualization of data, models, and predictions; Human behavioral predictions; Hardware-efficient machine learning methods; Model training, inference, and serving; Trust and security for machine learning applications; Testing, debugging, and monitoring of machine learning  applications; Machine learning for systems.

Specific Machine Learning approaches and Data Processing

Machine learning models (supervised, unsupervised, reinforcement, constrained, etc.); Generative modeling (Gaussian, HMM, GAN, Bayesian networks, autoencoders, etc.); Explainable AI (feature importance, LIME, SHAP, FACT, etc.); Bayesian learning models; Prediction uncertainty (approximation learning, similarity); Training of models (hyperparameter optimization, regularization, optimizers); Active learning (partially labels datasets, faulty labels, semi-supervised); Applications of machine learning (recommender systems, NLP, computer vision, etc.); Data in machine learning (no data, small data, big data, graph data, time series, sparse data, etc.)

Mechanisms and features

Scalable data analytics; Big data analytics; Deep data analytics; Mass data analytics; Storing, dropping and filtering data; Relevant/redundant/obsolete data analytics; Volume vs. semantics analytics; Nomad analytics; Predictive analytics; Trust in data analytics; Legal issues analytics; Failure on data analytics

Sentiment/opinion analysis

Architectures for generic sentiment analysis systems; Sentiment analysis techniques on social media; Document-level analysis; Sentence-level analysis; Aspect-based analysis; Comparative-sentiment analysis; Sentiment lexicon acquisition; Optimizing sentiment analysis algorithms; Applications of sentiment analysis.

Application-oriented analytics

Statistical applications; Simulation applications; Crawling web services; Cross-database analytics; Forecast analytics; Financial risk management; ROI analytics

Target analytics

Business analytics; Malware analytics; Cyber-threats analytics; Mining user logs; Reputation analytics; User choice analytics; Branding analytics; Utility proximity-search analytics; Survey-based online asset analytics; Online employment analytics; Geology analytics; Global climate analytics; Remote learning analytics; Homecare analytics; Population growth and migration analytics; Food-borne illness outbreaks analytics

Big Data

Foundational models for Big Data; Big Data Analytics and Metrics; Big Data processing and management; Big Data search and mining; Big Data platforms; Big Data persistence and preservation; Big Data and social networks; Big Data economics

Huge data

Knowledge Discovery from Huge Data; Computational Intelligence for Huge Data; Linked Huge Data; Security Intelligence with Huge Data

Deadlines: