2022年5月27日，吉林大学将继续举行“吉林大学~牛津大学前沿学术论坛“系列线上学术讲座，本次讲座由计算机科学与技术学院协办，王英教授主持，欢迎大家关注和参与!

报告题目；Knowledge Graphs——Challenges and Opportunities

报告时间：5月27日，18:00

报告方式：Zoom会议

会 议 码：898 6464 1932

登陆密码：2022

报 告 人：Bernardo Cuenca Grau 牛津大学教授

报告人简介：

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.

报告内容简介：

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.

主持人简介：

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.