DHA-based Knowledge Graph Construction
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Lei Chen
Department of Computer Science
Hong Kong University of Science and Technology
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Abstract
Recently, AI has become quite popular and attractive, not only to the academia but also to the industry.
The successful stories of AI on various of applications raise significant public interests on AI.
Meanwhile, human intelligence is turning out to be more sophisticated, and Big Data technology is everywhere to improve our life quality.
In this talk, I will discuss about DHA, a new computing paradigm, which combines big Data, Human intelligence, and AI (DHA).
Specifically, I will first briefly explain the motivation of the DHA.
Then I will present challenges, after that, I will present a case study to build a knowledge graph with the help of DHA.
Biography
Lei Chen has BS degree in computer science and engineering from Tianjin University, Tianjin, China, MA degree from Asian Institute of Technology, Bangkok, Thailand, and PhD in computer science from the University of Waterloo, Canada.
He is a professor in the Department of Computer Science and Engineering, Hong Kong University of Science and Technology (HKUST).
Currently, Prof. Chen serves as the director of Big Data Institute at HKUST, director of Master of Science on Big Data Technology and director of HKUST MOE/MSRA Information Technology Key Laboratory.
Prof. Chen's research interests include human-powered machine learning, crowdsourcing, Blockchain, graph data analysis, probabilistic and uncertain databases and time seires and multimedia databases.
Prof. Chen got the SIGMOD Test-of-Time Award in 2015.
The system developed by Prof. Chen's team won the excellent demonstration award in VLDB 2014.
Prof. Chen has served as VLDB 2019 PC Co-chair.
Currently, Prof. Chen serves as Editor-in-Chief of VLDB Journal, associate editor-in-chief of IEEE Transaction on Data and Knowledge Engineering.
He is an IEEE Fellow, ACM Distinguished Member and an executive member of the VLDB endowment.
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