Scope

Big data paradigm is an interdisciplinary field bringing together computer science, mathematics, statistics and information theory to analyze data for interpretation and prediction. Big data research is characterized by voluminous and incremental datasets and complex data methods. The machine learning methods used in algorithm development are iterative and parallel. These methods can be scaled to handle big data using distributed and parallel computing technologies. Recent technological advances allow for high throughput profiling of data analytics systems in a cost-efficient manner. The low cost of data generation is leading us to the big data era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. Integration of big data from multiple sources has evolved significantly in the era of post genomics and big data. Huge advancements were made toward storing, handling, mining, comparing, extracting, clustering and analysis as well as visualization of big data using novel computational approaches, machine and deep learning methods and web-based server tools.

BDCC 2020 addresses the issues and challenges posed by several big data problems and give an overview of the state of the art and the future research opportunities. BDCC 2020 is open to submit high quality research contributions from wide range of professions including scholars, researchers, academicians and Industry people. Original research papers and state of the art reviews will be accepted.

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Topics

The works that will be presented at conference will focus on the following topics:

- Data Science for Cognitive Analysis
- Real-Time Ubiquitous Data Science
- Signal Processing Architectures, Algorithms and Applications
- Algorithm development for big data analysis in E-health, telemedicine
- Biomedical Image Processing and Big Data Applications
- Platform for Privacy Preserving Data Science
- Internet-Based Cognitive Platform
- Social Data Relationship Ranking on Internet
- Data Applications of Cognitive Communication
- Green Technologies in Information, Computing and Big Communication Systems
- Statistics, Data Filtering to Decide What Data to Keep and Informative Aspects
- Machine Learning and Big Data
- Smart Vehicular Communication and Big Data Technology
- Bioinformatics and Big Data Computation
- Big Algorithms and Software Development
- Image Computing and Data Science Technology
- Smart Grid Cyber Security Data Analysis
- Smart City Initiative and Big Applications
- Natural Language Generation
- Sustainable Computer and Communication Model
- Knowledge Engineering, Representation and Extraction
- Cloud Big Computing Services
- Scalable Data Management Systems
- Future Advancements

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Publication

All registered papers will be submitted for publishing by Springer and made available through SpringerLink Digital Library.

Proceedings will be submitted for inclusion in leading indexing services, Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).

Authors of selected papers will be invited to submit an extended version to:
- Emerald – Data Technologies and Applications (Scopus Indexed)

All accepted authors are eligible to submit an extended version in a fast track of:
- Mobile Networks and Applications (MONET) Journal (IF: 2.390)
- Springer Wireless Networks (WINET) (IF: 2.405)
- International Journal of Cloud Computing (Scopus Indexed)
- Keai – Elsevier – International Journal of Intelligence Networks (IJIN)
- International Journal of Intelligence and Sustainable Computing

Additional publication opportunities:
- EAI Transactions series (Open Access)
- EAI/Springer Innovations in Communications and Computing Book Series