26 July, 2018Workshop on Big Graph and Spatial-Temporal Data Mining
Almost 200 students and researchers from HKUST and other institutes attended a workshop on Big Graph and Spatial-Temporal Data Mining organized by HKUST Big Data Institute (BDI) on 26 July 2018 in HKUST.
With the rapid technology development and growing use of smart sensors, smart devices and social media, a massive amount of big data can be generated and collected. Big Data has created a far-reaching impacts and challenges to scholars, researchers, scientists and many other professionals to develop new and efficient computing technologies for mining and analyzing the data. Graph data are key parts of big data and widely used for modelling complex structured data with a broad spectrum of applications.
The workshop started at 2:00 p.m. at LT-D, and the welcome speech was presented by Prof Lei Chen, Acting Director of BDI. He said big data is the fuel and engine of machine learning and AI, so that is the reason why BDI organized this workshop.
After then, another opening speech was presented by Prof DY Yeung, Acting Head and Professor, Department of Computer Science and Engineering, HKUST. He expressed appreciation to the speakers, and wished that they would provide their latest research results and share with us.
There were four excellent keynote speeches in the event, including "Unintended Consequences of Disclosing Location Data" by Prof Cyrus Shahabi, Professor of Computer Science, Electrical Engineering and Spatial Sciences & Chair, Department of Computer Science, University of Southern California. Prof Shahabi’s talk consisted of two parts. In the first part, he showed it is possible to infer social behaviors by observing people’s behaviors in the real world. In the second part of the talk, he showed how to hide user co-locations, without sacrificing the quality and effectiveness of services that finance the location-based applications.
"Towards Big Graph Processing: Applications, Challenges, and Advances" by Prof Xuemin Lin, Scientia Professor, FIEEE, Database Research Group, School of Computer Science and Engineering, University of New South Wales. In this talk, Prof Lin covered various applications, challenges, and recent advances, as well as future development of this area.
"Persistent Community Search in Temporal Networks" by Prof Jeffrey Xu Yu, Professor, Department of Systems Engineering and Engineering Management, the Chinese University of Hong Kong. Prof Xu discussed the problem of finding persistent communities in a temporal network, in which every edge is associated with a timestamp.
And "Mining Structured Knowledge from Massive Text Data: A Weakly Supervised Approach" by Prof Jiawei Han, Abel Bliss Professor, Department of Computer Science, University of Illinois at Urbana-Champaign. Prof Han introduced a set of methods developed recently in his research group on exploring the power of big text data, including mining quality phrases, recognition and typing of entities and relations by weak supervision, pattern-based entity-attribute-value extraction, multi-faceted taxonomy discovery, and construction of multi-dimensional text cubes.
The workshop was well received with loads of questions raised by the participants. Looking forward to seeing you in our future event!