Abbrevation
IEEE BigData
City
Los Angeles
Country
United States
Deadline Paper
Start Date
End Date
Abstract

<br>Example topics of interest includes but is not limited to the following:<br>1&#046; Big Data Science and Foundations<br>Novel Theoretical Models for Big Data<br>New Computational Models for Big Data<br>Data and Information Quality for Big Data<br>New Data Standards<br>2&#046; Big Data Infrastructure<br>Cloud/Grid/Stream Computing for Big Data<br>High Performance/Parallel Computing Platforms for Big Data<br>Autonomic Computing and Cyber&#8211;infrastructure, System Architectures, Design and Deployment<br>Energy&#8211;efficient Computing for Big Data<br>Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data<br>Software Techniques and Architectures in Cloud/Grid/Stream Computing<br>Big Data Open Platforms<br>New Programming Models for Big Data beyond Hadoop/MapReduce, STORM<br>Software Systems to Support Big Data Computing<br>3&#046; Big Data Management<br>Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data<br>Algorithms and Systems for Big Data Search<br>Distributed, and Peer&#8211;to&#8211;peer Search<br>Big Data Search Architectures, Scalability and Efficiency<br>Data Acquisition, Integration, Cleaning, and Best Practices<br>Visualization Analytics for Big Data<br>Computational Modeling and Data Integration<br>Large&#8211;scale Recommendation Systems and Social Media Systems<br>Cloud/Grid/Stream Data Mining&#8211; Big Velocity Data<br>Link and Graph Mining<br>Semantic&#8211;based Data Mining and Data Pre&#8211;processing<br>Mobility and Big Data<br>Multimedia and Multi&#8211;structured Data&#8211; Big Variety Data<br>4&#046; Big Data Search and Mining<br>Social Web Search and Mining<br>Web Search<br>Algorithms and Systems for Big Data Search<br>Distributed, and Peer&#8211;to&#8211;peer Search<br>Big Data Search Architectures, Scalability and Efficiency<br>Data Acquisition, Integration, Cleaning, and Best Practices<br>Visualization Analytics for Big Data<br>Computational Modeling and Data Integration<br>Large&#8211;scale Recommendation Systems and Social Media Systems<br>Cloud/Grid/StreamData Mining&#8211; Big Velocity Data<br>Link and Graph Mining<br>Semantic&#8211;based Data Mining and Data Pre&#8211;processing<br>Mobility and Big Data<br>Multimedia and Multi&#8211;structured Data&#8211;Big Variety Data<br>5&#046; Big Data Security, Privacy and Trust<br>Intrusion Detection for Gigabit Networks<br>Anomaly and APT Detection in Very Large Scale Systems<br>High Performance Cryptography<br>Visualizing Large Scale Security Data<br>Threat Detection using Big Data Analytics<br>Privacy Threats of Big Data<br>Privacy Preserving Big Data Collection/Analytics<br>HCI Challenges for Big Data Security &amp; Privacy<br>User Studies for any of the above<br>Sociological Aspects of Big Data Privacy<br>Trust management in IoT and other Big Data Systems<br>6&#046; Big Data Applications<br>Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication<br>Big Data Analytics in Small Business Enterprises (SMEs)<br>Big Data Analytics in Government, Public Sector and Society in General<br>Real&#8211;life Case Studies of Value Creation through Big Data Analytics<br>Big Data as a Service<br>Big Data Industry Standards<br>Experiences with Big Data Project Deployments<br>