The Third International Conference on Data Mining, Internet Computing, and Big Data (BigData 2016)

Key Topics

• Data Mining Integration & Process
  • Metadata and ontologies
  • Distributed and grid based data mining
  • Attribute discretization and encoding
  • Mining large scale data
  • Model interpretation
  • Feature selection and transformation
  • Data cleaning and preparation
• Data Mining Tasks & Algorithms
  • Mining text and semi-structured data
  • Explorative and visual data mining
  • Segmentation/Clustering/Association
  • Multimedia mining (audio/video)
  • Artificial neural networks
  • Web mining
  • Evolutionary computation/meta heuristics
  • Link and sequence analysis
• Internet Computing
  • Digital libraries/digital image collections
  • Design and analysis of internet protocols and engineering
  • Grid based computing and internet tools
  • Electronic commerce and internet
  • Internet and video technologies
  • Internet and emerging technologies
  • Internet banking systems
  • Internet applications and appliances
  • Internet law and compliance
  • Internet based decision support systems
  • Markup Languages
  • Internet security and trust
  • Mobile computing and the internet
  • Metacomputing
  • Novel Java applications on internet
  • Network architectures and network computing
  • Search engines
  • Quality of service
  • The WWW and intranets
  • Social networks
  • Web based computing
  • The internet and Cloud computing
  • Web site design and coordination
  • Web interfaces to databases
• Data Mining Applications
  • Business/Corporate/Industrial Data Mining
  • Bioinformatics
  • Data Mining in Logistics
  • Credit Scoring
  • Direct Marketing
  • Database Marketing
  • Medicine Data Mining
  • Engineering Mining
  • Security Data Mining
  • Military Data Mining
  • Time series analysis and visualization
  • Social Science Mining
  • Association rule learning
  • Anomaly detection
  • Cloud based infrastructure (applications, storage and resources)
  • Classification
  • Crowd-sourcing
  • Cluster analysis
  • Data-mining grids
  • Data fusion and integration
  • Distributed file systems
  • Distributed databases
  • Genetic algorithms
  • Ensemble learning
  • Massively parallel-processing (MPP) databases
  • Machine learning
  • Neural networks
  • Natural language processing
  • Predictive modeling
  • Pattern recognition
  • Sentiment analysis
  • Search-based applications
  • Simulation
  • Signal processing
  • Supervised and unsupervised learning

Who should Attend

Researchers in the fields of Data Mining, Internet Computing, and Big Data.