TOPICS OF INTEREST FOR SUBMISSION INCLUDE, BUT ARE NOT LIMITED TO:

 

Unsupervised Learning		Algorithms and Systems for Big Data Search
Meaningful Compression		Distributed, and Peer-to-peer Search
Computational Theories of Learning		Big Data Search Architectures, Scalability and Efficiency
Big Data Visualization		Data Acquisition, Integration, Cleaning, and Best Practices
Structure Discovery		Visualization Analytics for Big Data
Feature Elicitation		Computational Modeling and Data Integration
Recommender Systems		Large-scale Recommendation Systems and Social Media Systems
Targetted Marketing		Cloud/Grid/Stream Data Mining- Big Velocity Data
Multitasking and Transfer Learning		Link and Graph Mining
Customer Segmentation		Semantic-based Data Mining and Data Pre-processing
Deep learning		Mobility and Big Data
Supervised Learning		Multimedia and Multi-structured Data- Big Variety Data
Image Classification		Social Web Search and Mining
Identity Fraud Detection		Web Search
Customer Retention		Intrusion Detection for Gigabit Networks
Diagnositics		Anomaly and APT Detection in Very Large Scale Systems
Population Growth Prediction		High Performance Cryptography
Advertising Popularity Prediction		Visualizing Large Scale Security Data
Weather Forecasting		Threat Detection using Big Data Analytics
Market Forecasting		Privacy Threats of Big Data
Estimating Life Expectancy		Privacy Preserving Big Data Collection/Analytics
Intelligent Search		HCI Challenges for Big Data Security & Privacy
Data Access		User Studies for any of the above
Statistical Learning		Sociological Aspects of Big Data Privacy