2022年5月27日，伟德国际BETVlCTOR将繼續舉行“伟德国际BETVlCTOR~牛津大學前沿學術論壇“系列線上學術講座，本次講座由伟德国际BETVlCTOR協辦，王英教授主持，歡迎大家關注和參與!
報告題目；Knowledge Graphs——Challenges and Opportunities
報告時間：5月27日，18:00
報告方式：Zoom會議
會 議 碼：898 6464 1932
登陸密碼：2022
報 告 人：Bernardo Cuenca Grau 牛津大學教授
報告人簡介：
Professor Bernardo Cuenca Grau is a Professor at the Department of Computer Science, University of Oxford, and a Tutorial Fellow at Keble College, University of Oxford. Before joining Keble, he was a Supernumerary Fellow at Oriel College, University of Oxford, and up to October 2017, held a prestigious University Research Fellowship awarded by the British Royal Society. Professor Cuenca Grau obtained his Ph.D. in Computer Science from the University of Valencia, Spain in 2005. His research interests are in knowledge representation, ontologies and ontology languages, knowledge graph technologies, description logics, automated reasoning and applications in information systems and the Semantic Web. Professor Cuenca Grau received the Distinguished Paper Award at the 2017 International Joint Conference on Artificial Intelligence for his paper "Foundations of Declarative Data Analysis Using Limit Datalog Programs" and Best Paper Award at the 2010 AAAI Conference on Artificial Intelligence for his paper "How Incomplete is your Semantic Web Reasoner?".
His research is in the broad field of artificial intelligence. In particular, his work revolves around the areas of knowledge representation and reasoning, knowledge graphs, computational logic, semantic technologies, and their applications to data management and the Web. His activities within these areas cover a wide spectrum, including theory and foundations, algorithm design, software and systems, technology standards, and engagement with industry.
報告内容簡介：
Knowledge graphs use a graph-based data model to capture knowledge and data in application scenarios that involve integrating, managing and extracting value from diverse sources of data at large scale.
Since the announcement in 2012 of the Google Knowledge Graph initiative, followed by further announcements by other big technology players, research on knowledge graph technologies has received a great deal of attention in both academia and industry.
In this talk, Professor Cuenca Grau will discuss important challenges in knowledge graph research including knowledge graph creation and curation, logical reasoning on top of knowledge graphs, and graph representation learning.
主持人簡介：
Ying Wang is a Professor at the College of Computer Science and Technology in Jilin University. She obtained her Ph.D. from Jilin University in 2010, and her research interests are Machine Learning, Data Mining and Social Computing.
From September 2013 to September 2014, she studied as a visiting scholar at Arizona State University under the guidance of Professor Huan Liu（IEEE/ACM/AAAI FELLOW）. She has published more than 80 academic papers in KDD, WWW, AAAI, IJCAI, JCST, DKE, Information Sciences, etc., and presided 6 National and Provincial Projects.
