Knowledge Graphs (KGs) like Wikidata, NELL and DBPedia have recently played instrumental roles in several applications of computational intelligence, including search and information retrieval, natural language processing, and data mining. The simplest definition of a KG is as a directed, labeled multi-network. Yet, despite being ubiquitous in the communities mentioned above, the full scope of KGs has not been explored across the computational intelligence community. With the rapid rise in Web data, there are many interesting and domain-specific opportunities in this area. We propose a tutorial that will provide a detailed and rigorous synthesis of KGs, along with discussing the application potential of KGs across multiple domains within computational intelligence.
Expected learning outcomes and target audience. This tutorial will be specifically designed for students, researchers and applied scientists (whether in academia or industry) in computational intelligence who have an interest in seeking further intersection and insights with research in knowledge graphs and knowledge discovery in the broader NLP, semantic web and data mining communities. Participants will only be expected to have a very basic knowledge of machine learning.
This tutorial will be delivered by Dr. Mayank Kejriwal, a research assistant professor (Industrial and Systems Engineering) and research lead (Information Sciences Institute) at the University of Southern California. He is affiliated with the Center on Knowledge Graphs1 at USC/ISI. His research focuses on knowledge graphs (KG), an area of AI that has found widespread applications in industry (including Amazon and Google), academia (health informatics and social sciences) and for social causes (fighting human trafficking and crisis response). He has given talks and tutorials in international academic and industrial venues, most recently serving as a roundtable speaker and participant at the Concordia Summit that was co- held with the UN General Assembly in New York City in September, 2019. He is also the author of an MIT Press textbook on knowledge graphs, and he authored the popular Springer Brief ‘Domain-specific Knowledge Graph Construction’ in 2019.