Due to the current situation of COVID-19, the organizing committee decided to hold the 12th IEEE International Conference on Big Knowledge (ICBK-2021) again with Zoom. Please refer to the attachment ( ICBK2021-Programme.pdf ) for the detailed schedule of the conference, or visit the Program page to view it online.


Alan Bundy

University of Edinburgh

Title: Combining Deductive and Statistical Explanations in the FRANK Query Answering System.

Abstract: We will describe the hybrid FRANK query answering system (Functional Reasoner for Acquiring New Knowledge). FRANK infers new knowledge from the diverse and immense knowledge sources on the Web, using a combination of both deductive and statistical reasoning. This enables it to make predictions. For instance, to answer the question “Which country in Europe will have the highest GDP growth rate by 2032?”. It decomposes Europe into its constituent countries, then for each country uses regression over their previous GDP growth rates to extrapolate each to 2032 and then return the country which is predicted to then have the maximum value. The decompositions are explained deductively and the regressions graphically.

Both symbolic and sub-symbolic AI have their limitations, but their combination can be more than the sum of their parts. For instance, statistical machine learning has been hugely successful at classification and decision-making tasks, but not so good at deliberative systematic reasoning nor at explanation. We argue that by combining symbolic and sub-symbolic reasoning, as we do in the FRANK system, the whole will be more than the sum of its parts. Consider, for instance, the explanation of FRANK’s reasoning in the previous paragraph, merging deduction and statistics. We are currently expanding both the deductive and statistical components of FRANK to see how far this can take us.


Alan Bundy is Professor of Automated Reasoning in the School of Informatics at the University of Edinburgh. His research interests include: inferring new knowledge from the immense and diverse sources on the Web and the automatic construction, analysis and evolution of representations of knowledge. His research combines artificial intelligence with theoretical computer science and applies this to practical problems in the development and maintenance of computing systems. He is the author of over 300 publications and has held over 60 research grants.

He is a fellow of several academic societies, including the Royal Society, the Royal Society of Edinburgh, the Royal Academy of Engineering and the Association for Computing Machinery. His awards include the IJCAI Research Excellence Award (2007), the CADE Herbrand Award (2007) and a CBE (2012). He was: Edinburgh's founding Head of Informatics (1998-2001); founding Convener of UK Computing Research Council (2000-05); and a Vice President and Trustee of the British Computer Society with special responsibility for the Academy of Computing (2010-12). He was also a member of: the Hewlett-Packard Research Board (1989-91); the ITEC Foresight Panel (1994-96); both the 2001 and 2008 Computer Science RAE panels (1999-2001, 2005-8); and the Scottish Science Advisory Council (2008-12).

Yunjie Liu

Jiangsu Future Networks Institute and Purple Mountain Laboratory

Title: The Evolution of Future Network Technology

Abstract: The Internet Age is evolving from being consumer-oriented to production-oriented. The state-of-the-art TCP/IP technology stack still cannot meet the differentiated, customized, and highly-précised networking requirements of the future services, such as Industrial Internet and Internet of Vehicles. SCN (Service Customized Networking), first proposed by our team in 2014, aims at solving these problems systematically. SCN is technically based on SDN and White-Box Switching, and has formed a self-contained system architecture and roadmap, focusing on the new network carrier, network operating system, and cloud-network hyper-convergence. We have been studying and practicing SCN over CENI (China Experimental Networking Infrastructure) for years. This presentation will introduce our latest research progress of SCN and CENI.

Mr. Yunjie Liu, a Member of the Chinese Academy Engineering, is now Director of Jiangsu Future Networks Institute and Director of the Purple Mountain Laboratory. He also serves as project leader of the major technology infrastructure of the China Environment Networking Innovation (CENI). He was honored with a Special Contribution Award for "Persons of the Year 2014 for China’s Internet". Mr. Liu played a leading role in the design, construction and operation of the national public data network and high-speed broadband, which laid an important foundation for the construction of information society in China. He has received a first grade National Prize for Achievements in Science & Technology, and twice the first grade Ministerial Prize for Achievements in Science & Technology. Having committed in network technology for almost four decades, Mr. Liu has been pioneering in data networks and Internet and network integration.

Weimin Zheng

Tsinghua University

Title: What to Expect for the Next Generation Distributed File Systems?

Abstract: Applications such as artificial intelligence, big data, and graph computing are putting extreme demands on the I/O performance of storage systems. In addition, with the rapid increase in the performance of storage and networking devices, the existing storage system software stack is becoming increasingly complex and difficult to meet the applications demand for high performance. Perhaps now is time to rebuild distributed file systems from scratch to harness the power of the underlying hardware and fulfill the demands from the applications. In this presentation I will talk about different aspects of storage systems, including high performance, high reliability, high efficiency, and also how architectures of distributed file systems are evolving in recent years. I will also share our experiences in building the next-generation distributed file systems.

Weimin Zheng is a professor in the Department of Computer Science and Technology at Tsinghua University. He is a member of the Chinese Academy of Engineering. He has long been engaged in high-performance computer architectures, parallel algorithms, and storage systems. He has proposed several key technologies for high-performance storage systems. He is a pioneer in high-performance computer architectures to develop and successfully apply cluster architecture high-performance computers in China. He has helped to develop extremely large-scale weather forecasting applications to run on the domestic Shenwei TaihuLight, which won the ACM Gordon Bell Award. He won several national awards, including the First Prize and Second Prize of the National Science and Technology Progress Award, the Second Prize of the National Technical Invention Award, the He Liang He Li Award for Scientific and Technological Progress, and the First China Storage Lifetime Achievement Award.

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