Semantic Computing Laboratory Introduction
The Semantic Computing Lab of Shandong University focuses on the fundamental theories and key technologies for big data semantic computing, as well as the applications in the fields of Social Computing, Collaborative Computing and Cognitive Computing.
Semantic Computing combines disciplines such as computational linguistics, artificial intelligence, database and services computing together into an integrated theme while addressing their synergetic interactions. The semantic technologies address the meaning of large-scale heterogeneous data and how they can help improve design for human centered inference task and develop intelligent software.
In recent years, we take on many important government and enterprise projects, including the National Natural Science Foundation of China, the National Key R&D Program of China，the National High Technology Research and Development Program of China (863 Program), the National Science and Technology Support Plan, the National development and Reform Commission Project, the Major Science and Technology Development Projects of Shandong Province, the Natural Science Foundation of Shandong Province, etc. We have released a number of applications in the related fields.
The head of lab is Dr. Sun Yuqing, the professor of Shandong University, who is also the deputy director of Technical Committee on Cooperation Computing of China Computer Federation (CCF), a member of the Technical Committee on Software Committee of CCF, a member of Shandong Electronic Government Affairs Expert Advisory Committee. She has published more than 80 research papers on prestigious international journals and conferences and serves as the chairman or a PC member of many international and national conferences, as well as the guest editor or a reviewer for more than 20 academic journals, such as IEEE Transaction on Dependable and Secure Computing, International Journal of Computers and Applications, Springer Information Systems Frontiers, Chinese Journal of Software, Chinese Journal of Computer, etc.
l Research Topics
Ø Natural Language Inference
Ø Extraction of the Structured Knowledge
Ø Controllable Text Generation
Ø Professional Text Understanding towards Academic Networks
Ø Correlation Analysis and Complex Inference based on Knowledge Graphs
l Published Papers