Global datasphere is increasing fast, and it is expected to reach 175 Zettabytes by 20251 . However, most of the content is unstructured and is not understandable by machines. Structuring this data into a knowledge graph enables multitudes of intelligent applications such as deep question answering, recommendation systems, semantic search, etc. The knowledge graph is an emerging technology that allows logical reasoning and uncovers new insights using content along with the context. Thereby, it provides necessary syntax and reasoning semantics that enable machines to solve complex healthcare, security, financial institutions, economics, and business problems. As an outcome, enterprises are putting their effort into constructing and maintaining knowledge graphs to support various downstream applications. Manual approaches are too expensive. Automated schemes can reduce the cost of building knowledge graphs up to 15-250 times. This paper critiques state-of-the-art automated techniques to produce knowledge graphs of near-human quality autonomously. Additionally, it highlights different research issues that need to be addressed to deliver high-quality knowledge graphs

Optimizing the utilization of berth space in a container yard has a direct impact to operations bottom line. Each additional container vessel that it can handle may add millions to revenue. Our optimization software not only captures business and operational rules and constraints, it also allows the user to perform what-if analysis and problem solving. Using optimization and resource allocation technologies plus dynamic decision-making and problem solving-capabilities, we were able to show an increase in overall productivity and efficiency in the container yard. Modern Terminals Limited is the longest established and one of the leading container terminal operators in Hong Kong, opening the territory's first purpose-built container terminal in September 1972.