Bigdata 2015 - 2015 INTERNATIONAL SYMPOSIUM ON BIG DATA AND DATA SCIENCE

Topics of interest include, but are not limited to the following
Algorithms for Big Data:
Data and Information Fusion; Algorithms (including Scalable methods); Natural Language Processing; Signal Processing; Simulation and Modeling; Data-Intensive Computing; Parallel Algorithms; Testing Methods; Multidimensional Big Data; Multi-linear Subspace Learning; Sampling Methodologies; and 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; and Computational Intelligence.
Data Science:
Conversion of Data to Information; Conversion of Data to Knowledge; Data Mining; Information Mining; Predictive Analytics; Knowledge Discovery; Cloud Computing; Databases and Information Integration; Signal Processing; Natural Language Processing; Information Retrieval Methods; and Information Visualization.
Infrastructures for Big Data & Data Science:
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 & Data Science 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; Novel Data Management Methods; Crowdsourcing; Stream Data Management; and Scientific Data Management.
Big Data Search:
Multimedia and Big Data; Social Networks; Web Search and Information Extraction; Scalable Search Architectures; Cleaning Big Data (noise reduction), Acquisition & Integration; Visualization Methods for Search; Time Series Analysis; Recommendation Systems; and Graph Based Search and Similar Technologies.
Security & Privacy in the Era of Data Science & 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