On the morning of June 15, the first lecture of the "HUST-NTU Academic Lecture Series" was held online. Invited by Professor Wei Wei, School of Computer Science and Technology, Huazhong University of Science and Technology(HUST), Professor Gao Cong, School of Computer Science and Engineering, Nanyang Technological University(NTU), delivered an online speech on the topic of"Enriched Spatial Data Management and Trajectory Data Mining". The lecture was hosted by Professor Wei Wei and attracted more than 500 researchers and students from NTU, HUST, and other universities to attend the online conference.
Contents of the Report:
Professor Cong believes that with the popularity of GPS devices, a large amount of geospatial data is being generated on an unprecedented scale. In this report, Professor Cong introduced the research overview of geospatial data mining and management and gave a specific introduction to two related topics. The first is to query rich spatial data, and the second is about trajectory data mining, such as trajectory similarity calculation, trajectory simplification, and intelligent transportation applications.
In addition, Professor Cong also introduced the specific categories of rich spatial data: Data is not only concentrated in spatial attributes but also other attributes, such as images and videos; Not only static data but also data related to data streams such as microblogs. After that, Professor Cong introduced the corresponding data management work in detail, such as adopting some distributed systems or methods to support the query or processing of data flow and solving the problems such as load balancing that may exist in it. Professor Cong said that according to the form of spatial data, data could be divided into three types: Point, track, and region. There are different tasks of data mining and data analysis for the three kinds of data, and different applications.
After that, Professor Cong carefully explained how to build a distributed query method for querying streaming spatial textual data (SSTD) with multiple attributes, and then focused on the introduction of track type data, such as the method of trajectory similarity calculation, and finally briefly introduced the related intelligent transport applications.
In the discussion session, Professor Cong patiently answered the questions of the teachers and students attending the meeting, summarized the current research direction and methods of trajectory data mining, and analyzed that the next research hotspot is the integration of other data for joint mining, as well as the optimization of the storage and query methods of trajectory itself.
Introduction of the Speaker
Gao Cong is currently a professor at the School of Computer Science and Engineering of NTU, and a co-director for Singtel Cognitive and Artificial Intelligence Lab.
He received his Ph.D. in Computer Science from NUS in 2004, and From 2004 to 2006, he worked as a postdoc at the University of Edinburgh. Before joining NTU, he was an Assistant professor at Aalborg University, Denmark. Before that, he worked as a researcher at Microsoft Research Asia. His general research interests are in Data Science.
In particular, his research focuses on geospatial data management, Spatio-temporal data mining, recommendation, and mining social media. He has published in prestigious journals (e.g., VLDB Journal, TODS, TKDE) and conferences (e.g., VLDB, SIGMOD, ICDE, KDD, WSDM, SIGIR, WWW). His paper won the Best Paper Award in WSDM'20 and WSDM'22, and his citation in Google Scholar was over 14000 with an H-index of 61.
He served as a PC co-chair for ICDE'22, Associate General Chair for KDD'21, a PC co-chair for the E&A track of VLDB 2014, and a PC vice-Chair for ICDE'18.
He is an associate editor for ACM Transactions on Database Systems (TODS) and the vice Chair of the ACM KDD Singapore chapter.
Introduction of NTU
Nanyang Technological University (NTU) is a world-renowned research university in Singapore. The university is a member of the Association of Pacific Rim Universities, the International Alliance for New Engineering Education, the founding member of Global AI Academic Alliance, the AACSB-accredited member, and the founding member of the Global Alliance of Technological Universities. As a research-intensive university in Singapore, it enjoys a world reputation for its research in many fields such as nanomaterials, biomaterials, chemistry, electrical engineering, and mechanical and aerospace engineering. NTU is ranked 1st in the QS World Young University Rankings 2021, 2nd in the QS Asian University Rankings 2020, and 3rd in THE World Young University Rankings 2019.
