Topics of Interest

  Topics covering industrial issues/applications and academic research into big knowledge will be included, but not limited to:

  1. Foundations, algorithms, models, and theory of big knowledge engineering

  2. Machine learning and statistical methods for big knowledge engineering

  3. Acquisition, representation and evolution of fragmented knowledge

  4. Fragmented knowledge modeling and online learning, topology and fusion on     fragmented knowledge

  5. Visualization, personalization, and recommendation of big knowledge navigation and interaction

  6. Big knowledge engineering systems and platforms, their efficiency, scalability, and privacy 

  7. Applications and services of big knowledge in all domains including web, medicine, education, healthcare, and business