Y
Yuefeng Li
Researcher at Queensland University of Technology
Publications - 307
Citations - 5192
Yuefeng Li is an academic researcher from Queensland University of Technology. The author has contributed to research in topics: Ontology (information science) & Recommender system. The author has an hindex of 35, co-authored 297 publications receiving 4581 citations. Previous affiliations of Yuefeng Li include City University of Hong Kong & University of Queensland.
Papers
More filters
Journal ArticleDOI
Effective Pattern Discovery for Text Mining
TL;DR: This paper presents an innovative and effective pattern discovery technique which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information.
Journal ArticleDOI
Mining ontology for automatically acquiring Web user information needs
Yuefeng Li,Ning Zhong +1 more
TL;DR: The objective of the approach is to automatically discover ontologies from data sets in order to build complete concept models for Web user information needs and a method for capturing evolving patterns to refine discovered ontologies is proposed.
Journal ArticleDOI
Text mining and probabilistic language modeling for online review spam detection
TL;DR: The work discussed in this article represents the first successful attempt to apply text mining methods and semantic language models to the detection of fake consumer reviews.
Journal ArticleDOI
Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning
TL;DR: The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm which can automatically construct concept maps based on the messages posted to online discussion forums.
Journal ArticleDOI
The state-of-the-art in personalized recommender systems for social networking
TL;DR: An overview of existing technologies for building personalized recommender systems in social networking environment is given, and a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0 is proposed.