
Professor Yuefeng Li
Science and Engineering Faculty,Electrical Engineering, Computer Science,
Data Science
Personal details
- Name
- Professor Yuefeng Li
- Position(s)
- Professor
Science and Engineering Faculty,
Electrical Engineering, Computer Science,
Data Science - Discipline *
- Artificial Intelligence and Image Processing, Information Systems
- Phone
- +61 7 3138 5212
- y2.li@qut.edu.au
- Location
- View location details (QUT staff and student access only)
- Identifiers and profiles
-
- Qualifications
-
PhD (Deakin University)
- Keywords
-
Data Mining, Knowledge and Data Engineering, Web Intelligence, Knowledge-based systems
Biography
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:
- Text mining and analysis
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.
Teaching
Teaching in 2011:
INB343 (INN343) – Advanced Data Mining and Data Warehousing
INB302 – IT Capstone Project
Publications
- Li Y, Zhang L, Xu Y, Yao Y, Lau RY, Wu Y, (2017) Enhancing binary classification by modeling uncertain boundary in three-way decisions, IEEE Transactions on Knowledge and Data Engineering p1438-1451
- Li Y, Algarni AE, Albathan M, Shen Y, Bijaksana A, (2015) Relevance feature discovery for text mining, IEEE Transactions on Knowledge and Data Engineering p1656-1669
- Li Y, Wu J, (2014) Interpretation of association rules in multi-tier structures, International Journal of Approximate Reasoning p1439-1457
- Li Y, Zhou X, Bruza P, Xu Y, Lau R, (2012) A two-stage decision model for information filtering, Decision Support Systems p706-716
- Zhong N, Li Y, Wu S, (2012) Effective pattern discovery for text mining, IEEE Transactions on Knowledge and Data Engineering p30-44
- Tao D, Li Y, Zhong N, (2011) A Personalized Ontology Model for Web Information Gathering, IEEE Transactions on Knowledge & Data Engineering p496-511
- Li Y, Algarni A, Zhong N, (2010) Mining positive and negative patterns for relevance feature discovery, Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining p753-762
- Li Y, Zhou X, Bruza P, Xu Y, Lau R, (2008) A two-stage text mining model for information filtering, Proceedings of the ACM 17th Conference on Information and Knowledge Management (CIKM2008) p1023-1032
- Li Y, Zhong N, (2006) Mining Ontology for Automatically Acquiring Web User Information Needs, IEEE Transactions on Knowledge and Data Engineering p554-568
- Li Y, Zhong N, (2004) Web Mining Model and its Applications for Information Gathering, Knowledge Based Systems p207-217
For more publications by this staff member, visit QUT ePrints, the University's research repository.
Awards
Awards and recognition
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2012
- Details
- Best Paper Award "Personalization in Tag Ontology Learning for Recommendation Making", 14th International Conference on Information Integration and Web-Based Applications & Services, 3-5 December 2012, Ball, Indonesia.
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2008
- Details
- Best Paper Award, "Web information recommendation making based on item taxonomy", 10th International Conference on Enterprise Information Systems, June 2008, Barcelona, Spain, 2008.
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2007
- Details
- Outstanding Doctoral Thesis, "Knowledge discovery using pattern taxonomy model in text mining", Sheng-Tang Wu (Supervisors: Prof Yuefeng Li and A/Prof Yue Xu), QUT, 2007.
Research projects
Grants and projects (Category 1: Australian Competitive Grants only)
- Title
- Automatic Ontology Learning and Data Reasoning in Web Mining
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP0556455
- Start year
- 2005
- Keywords
- Web intelligence Web mining Ontology learning Data mining Data reasoning Information filtering
- Title
- Web Services Reputation Management
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP0776400
- Start year
- 2007
- Keywords
- Web Services; Reputation; Trust Management; Security; Quality of Service; Service Oriented Architecture
- Title
- Personalized Ontology Learning And Mining For Web Information Gathering
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP0988007
- Start year
- 2009
- Keywords
- Web intelligence; Ontology learning; Ontology mining; Information gathering; Personalization;
- Title
- A Framework for Scalable Ontology Enrichment and Change
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP130102302
- Start year
- 2013
- Keywords
- Knowledge Representation; Ontology Change; Description Logics
- Title
- Learning Specific Ontology for Un-Supervised Text Classification
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP140103157
- Start year
- 2014
- Keywords
- Text feature extraction; Ontology learning; Data mining
Supervision
Completed supervisions (Doctorate)
- A Data Mining Approach to Improve the Automated Quality of Data (2014)
- A Data Mining Framework for Relevance Feature Discovery (2013)
- Personalized Ontology Learning for Enhancing Text Mining Effectiveness (2013)
- Relevance Feature Discovery For Text Analysis (2011)
- User Profiling based on Folksonomy information in Web 2.0 for Personalised Recommender Systems (2011)
- Granule-Based Knowledge Representation for Intra and Inter Association Mining (2009)
- Personalised Ontology Learning and Mining for Web Information Gathering (2009)
- Rough Set-based Reasoning and Pattern Mining for Information Filtering (2009)
- Search Engine Content Analysis (2008)
- Knowledge Discovery using Pattern Taxonomy Model in Text Mining (2007)