International Symposium on Foundations and Applications of Big Data Analytics
Big Data is an emerging research trend in many disciplines. The Big Data research includes challenges like analysis, capture, curation, search, sharing, storage, transfer, visualization, and privacy violations. The trend to larger data sets equates to additional information that could be derived from analysis of a single large set of related data, as well as comparing and correlating information from more than one datasets that allow correlations to be found to spot business trends, prevent diseases, combat crime, customer behaviour patterns and many more. To build and enable infrastructures to handle and process Big Data may need to focus on velocity, variety, volume, variability, veracity and complexity of large-scale datasets.
Accepted and presented papers will be included in the FAB 2018 Conference Proceedings and forwarded for inclusion in IEEE Computer Society Digital Library (CSDL), IEEE Xplore and the ACM Digital Library. The conference proceedings will be submitted for EI indexing through INSPEC by IEEE. The proceedings will be also covered by several other indexes, including DBLP, SCOPUS, etc.
High-quality research papers accepted for publication in the conference proceedings will be invited to submit an extended version for a book to be published in Springer's Lecture Notes in Social Networks (LNSN) series, subject to additional peer reviewing.
Topics may include but not limited to:
Big Data Foundations
- Algorithms for Big Data
- Methodology for Big Data
- Infrastructure for Big Data
- Platforms for Big Data
- Models for Big Data
- Analytics for Big Data
- Mining for Big Data
- Management of Big Data
- Storage for Big Data
- Querying for Big Data
- Consistency for Big Data
- Big Data applications in Government sector
- Big Data applications in Science and Research
- Big Data applications in Industry
- Big Data applications in Education
- Big Data applications for Individual users
- Tools, techniques for Big Data Handling
- Tools, techniques for Big Data Management
- Tools, techniques for visualization of Big Data
- Tools, techniques for querying of Big Data
- Tools, techniques for storage of Big Data
- Tools, techniques for optimization of Big Data