Professor Yuefeng Li is the leader of AI-Based Data Analysis Group in the School of Electrical Engineering and Computer Science, QUT. He has published over 190 refereed papers (including 60 journal papers). He has demonstrable experience in leading large-scale research projects and has achieved many established research outcomes that have been published and highly cited in many significant Journals and Conferences. He has been a program chair of several International Conferences and workshops. He is the Editor-in-Chief of Web Intelligence Journal. Research Areas:
His contributions comprise pattern based models and relevance feature discovery to improve the effectiveness of information filtering. Another major contribution has been introducing theory and model into text classification research and document summarization from the field of three-way decision theory.
- Topic Modelling and Feature Selection
His contributions include models for integrating LDA (Latent Dirichlet Allocation, a famous topic modelling method) and pattern mining, and using extended random sets to interpret latent LDA topics to enhance the performance of topic modelling and feature selection.
- Ontology Learning and Web Intelligence
Ontology learning is an automatic or semi-automatic process for building of ontologies (knowledge bases) to enhance text analysis and support conversation between machine and human being. His contributions comprise ontology learning frameworks for information gathering and a new methodology for personalized ontology construction and its application for the interpretation of text mining results.
- Foundations of Data mining
His contributions include algorithms for mining non-redundant rules and a theory for extending association rule mining and clustering into granule mining.
This information has been contributed by Professor Yuefeng Li.
