In the last decade, in the Semantic Web field, knowledge bases have attracted tremendous interest from both academia and industry and many large knowledge bases are now available. In order to cope with this issue, the availability of automatic methods for schema aware generation and population of knowledge bases results fundamental. The primary goal of the special issue is to provide novel machine learning/data mining methods for knowledge base generation, population, enrichment, evolution showing advances in the Semantic Web field. Please indicate in the cover letter that it is for the Special Issue on Machine Learning for Knowledge Base Generation and Population.
The challenge also increases when AI systems are interacting in complex ways with other separately-developed AI systems that are themselves learning and adapting. The workshop, scheduled for June 28th, 2016, will include keynote talks and panel discussions that explore the potential future of AI and AI applications, the emerging technical means for constructing safe and secure systems, how safety might be assured, and how we can make progress on the challenges of safety and control for AI. In other words, how can we construct productive collaborations of the AI technical community, the application community, and the assurance community? In preparation for the technical workshop event, Carnegie Mellon will publish an open solicitation for white papers related to the workshop topics.