FAB 2017 - 2017 International Symposium on Foundations and Applications of Big Data Analytic

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 2017 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
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
Industrial Tools
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