Prof. Enhong Chen (winner of the National Science Fund for Distinguished Young Scholars (in 2013), who is the vice dean of School of Computer Science of USTC, gave a talk on December 17th in Xianlin campus, Nanjing Normal University. The topic of this talk is “Intelligent recommendation methods based on education big data”. Prof. Ming Yang hosted the talk.
Prof. Enhong Chen is the vice dean of School of Computer Science of University of Science and Technology of China(USTC), CCF Fellow, IEEE Senior Member (Since 2007), and winner of the National Science Fund for Distinguished Young Scholars (in 2013). He is also the vice director of the National Engineer Laboratory for Speech and Language Information Processing, the director of Anhui Province Key Laboratory of Big Data Analysis and Application, and the chairman of Anhui Province Big Data Industry Alliance.
His current research interests are data mining and machine learning, especially social network analysis and recommender systems. He has published more than 150 papers on many journals and conferences, including international journals such as IEEE Trans, ACM Trans, and important data mining conferences, such as KDD, ICDM, NIPS. My research is supported by the National Natural Science Foundation of China, National High Technology Research and Development Program 863 of China, etc. He won the Best Application Paper Award on KDD2008 and Best Research Paper Award on ICDM2011.
During the talk, Prof. Chen mainly introduced the research issues and the related works in the education big data, recommendation system and education big data for recommendation system. Also, he shared several novel works of his team for deep semantic understanding framework in education resources: a local-resources-based semantic relation inference model and an attention-based question representation model, which have been successfully applied to the IFTEC online education system.
After the talk, Prof. Chen had a discussion with the audiences and answered their questions in details. This talk enables the teachers and graduates to improve their understanding of the intelligent recommendation system for education big data. It also provides valuable suggestions and much inspiration for our researchers.