题目：Constructing and Reasoning with Open KnowledgeGraphs
主讲人：Jeff Z.Pan 教授 University of Aberdeen, UK
时间：上午10:00am - 10:30am
Knowledge Graph has shown to be useful in a number of application areas, such as semantic search, data integration, fake news detection and recommendation. While domain specific knowledge graphs are useful within specific domains, open knowledge graphs such as DBPedia, YAGO and Wikidata, have recently played instrumental roles in a number of applications. They can not only been used as common sense knowledge for machine learning applications but also asas reusable knowledge to complement domain specific knowledge graphs. In this talk, I will introduce knowledge graphs, in particular some well known open, including DBPedia, YAGO and Wikidata, and their applications, and discuss about existing reasoning techniques for large scale open knowledge graphs.
Jeff Z. Pan is a full professor in the University of Aberdeen, UK. Prof Dr Pan’s research focuses primarily on knowledge representation, artificial intelligence and data science, in particular knowledge graph construction and maintenance, large-scale ontology reasoning, stream reasoning, and combinations ontology reasoning with machine learning, as well as their applications. He is a key contributor of the W3C OWL (Web Ontology Language) standard. He leads the development of the award-wining TrOWL reasoner, the only ontology reasoner that Oracle Spatial and Graph (from v12) uses via the OWL-DBC database connection. He is an internationally leading expert on Knowledge Graph, being the Chief Editor of the first two books on Knowledge Graph, a new technology that is widely used by world leading IT companies. As the Chief Scientist and Coordinator of the EU Marie-Curie K-Drive project, he coordinated 22 Marie Curie Fellows on Knowledge Graph and Ontology research. He is an Associate Editor of the International Journal on Semantic Web and Information Systems (IJSWIS), and an Area Editor of the Journal of Web Semantics (JWS). He actively teams up with industrial collaborators on innovative research. For example, he works with IBM Research on knowledge graph learning and reasoning for cognitive computing systems; he works with Accenture Lab on reasoning enabled learning for e.g. flight delay forecasting, air quality forecasting and bus delay forecasting.