Knowledge representation is a significant branch of Artificial intelligence. It studies the formalization of knowledge and its processing within machines. Techniques of automated reasoning allow a computer system to draw conclusions from knowledge represented in a machine-interpretable form.Semantic networks provide a means to abstract from natural language, representing the knowledge that is captured in the text in a form more suitable for computation.The lack of semantics increases the possibility of misinterpretation of the information/data. This plays a very important role in data mining.  Application of Semantic technologies using the concepts of semantics, ontology, linked-data, and knowledge-graphs play such an important role in helping us understand the meaning of the data we possess. This gives us a better way of not only understanding our data, but representing them effortlessly.

Instructor's Bio

Emeka Okoye, Knowledge Scientist at Cymantiks Limited

Emeka Okoye is a Knowledge Scientist with Cymantiks Limited, a company that makes People, Organizations and Cities smarter using Semantic technologies for contextual data modeling, knowledge representation, and ontology engineering to exploit the opportunities possessed by Artificial Intelligence, Analytics, Machine Learning for Digital Transformation that will enable them to be data-driven.In the last 25 years, Emeka has been at the forefront of technology and innovation in Nigeria from co-founding the earliest startup ( to designing the first framework for publishing Open Election Data to building cognitive solutions like Knowledge Graph for public sector corruption.


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    Knowledge Representation and Reasoning with Semantic Web Technologies

    • Webinar Recording