Scope
Last modified
2014-12-16 01:35
Topics of interest include, but are not limited to,
the following:
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SCOPE: Topics of interest include, but are not limited to, the following:
Prologue: Big Data is the collection and compilation of data sets
that are so large that it becomes difficult and challenging to process
using conventional or standard methods. Big Data is a moving target;
what is Big now will not be considered Big in the future. Therefore,
scalability of methods and algorithms is an important part of any
solution. Note that papers that do not focus exclusively or primarily
on Big Data should not be submitted to this conference. For example,
papers that contribute to the areas of data mining and/or machine
learning should be submitted to the DMIN'15 International Conference,
PPPPPPweb link; ABDA'15 is not the right forum for topics in data
mining). Papers that address any of the following topics in the context
of Big Data are of interest.
- 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
- 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 Science
- Novel Data Management Methods
- Crowdsourcing
- Stream Data Management
- Scientific Data Management
- BIG DATA SEARCH:
- Multimedia and Big Data
- Social Networks
- Data Science
- Web Search and Information Extraction
- Scalable Search Architectures
- Cleaning Big Data (noise reduction), Acquisition & Integration
- Visualization Methods for Search
- Time Series Analysis
- Recommendation Systems
- Graph Based Search and 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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