World Conference on Big Data aims to bring together academicians, researchers, engineers, system analysts, software developers, graduate and undergraduate students with government and non-government organizations to share and discuss both theoretical and practical knowledge about  cloud computing turning computing and software into commodity services, everything as a service in other words, it leads to not only a technology revolution but also a business revolution. Insights and impacts of various types of services (infrastructure as a service, platform as a service, software as a service, and business process as a service) have to be re-examined.

The scope of the conference includes, but is not limited to; the following major topics;

  • ALGORITHMS FOR BIG DATA:
        – Data and Information Fusion
        – Genetic Algorithms
        – Machine Learning
        – Natural Language Processing
        – Signal Processing
        – Scalable Algorithms
        – Simulation and Modeling
        – Data-Intensive Computing
        – Parallel Algorithms (including the map-reduce paradigm)
        – Testing Methods
        – Dimensionality Reduction Techniques
        – Multidimensional Big Data
        – Multilinear Subspace Learning
        – Sampling Methodologies
        – Streaming
  • BIG DATA FUNDAMENTALS:
        – Novel Computational Methodologies
        – Algorithms for Enhancing Data Quality
        – Models and Frameworks for Big Data
        – Graph Algorithms and Big Data
        – Computational Science
        – Computational Intelligence
  • INFRASTRUCTURES FOR BIG DATA:
        – Cloud Based Infrastructures (applications, storage & computing resources)
        – Grid and Stream Computing for Big Data
        – High Performance Computing, Including Parallel & Distributed
        Processing – Autonomic Computing
        – Cyber-infrastructures and System Architectures
        – Programming Models and Environments to Support Big Data
        – Software and Tools for Big Data
        – Big Data Open Platforms
        – Emerging Architectural Frameworks for Big Data
        – Paradigms and Models for Big Data beyond Hadoop/MapReduce, …
  • BIG DATA MANAGEMENT AND FRAMEWORKS:
        – Database and Web Applications
        – Federated Database Systems
        – Distributed Database Systems
        – Distributed File Systems
        – Distributed Storage Systems
        – Knowledge Management and Engineering
        – Massively Parallel Processing (MPP) Databases
        – Novel Data Models
        – Data Preservation and Provenance
        – Data Protection Methods
        – Data Integrity and Privacy Standards and Policies
        – Data Fusion and Integration
        – Data Science
        – Novel Data Management Methods
        – Crowdsourcing
        – Stream Data Management
        – Scientific Data Management
  • BIG DATA SEARCH & MINING METHODS:
        – Multimedia and Big Data
        – Data Mining
        – Social Networks
        – Data Science
        – Web Search and Information Mining
        – Scalable Search Architectures
        – Cleaning Big Data (noise reduction), Acquisition & Integration
        – Visualization Methods for Search
        – Time Series Analysis
        – Recommendation Systems
        – Graph Mining and Other Similar Technologies
  • SECURITY & PRIVACY IN THE ERA OF BIG DATA:
        – Cryptography
        – Threat Detection Using Big Data Analytics
        – Privacy Threats of Big Data
        – Privacy Preserving Big Data Collection
        – Intrusion Detection
        – Socio-economical Aspect of Big Data in the Context of Privacy and Security
  • APPLICATIONS OF BIG DATA:
        – Big Data as a Service
        – Big Data Analytics in e-Government and Society
        – Applications in Science, Engineering, Healthcare, Visualization, Business, Education, Security, Humanities, Bioinformatics, Health Informatics, Medicine, Finance, Law, Transportation, Retailing, Telecommunication, all Search-based applications, …
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