J
Jiuyong Li
Researcher at University of South Australia
Publications - 335
Citations - 6808
Jiuyong Li is an academic researcher from University of South Australia. The author has contributed to research in topics: Computer science & Association rule learning. The author has an hindex of 38, co-authored 285 publications receiving 5280 citations. Previous affiliations of Jiuyong Li include Kunming University of Science and Technology & Griffith University.
Papers
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Journal ArticleDOI
Time to infer miRNA sponge modules
TL;DR: In this paper, the authors provide a comprehensive perspective of miRNA sponge module discovery methods and discuss the future directions and associated challenges in developing in silico methods to infer miRNA sponges.
Proceedings ArticleDOI
Efficient discovery of de-identification policy options through a risk-utility frontier
TL;DR: This work introduces a semantic definition of utility, based on information theory, that is compatible with the lattice representation of policies and builds the optimal set of policies that trade-off between privacy risk (R) and utility (U), which is referred to as a R-U frontier.
Journal ArticleDOI
Using multiple and negative target rules to make classifiers more understandable
Jiuyong Li,Jason Jones +1 more
TL;DR: This paper proposes to use multiple and negative target rules to improve explanatory ability of rule based classifiers and shows experimentally that this understandability is not at the cost of accuracy of rulebased classifiers.
Book ChapterDOI
L-Diversity Based Dynamic Update for Large Time-Evolving Microdata
Xiaoxun Sun,Hua Wang,Jiuyong Li +2 more
TL;DR: This paper investigates the problem of updating large time-evolving microdata based on the sophisticated l -diversity model, in which it requires that every group of indistinguishable records contains at least l distinct sensitive attribute values; thereby the risk of attribute disclosure is kept under 1/l.
Journal ArticleDOI
Inferring functional miRNA-mRNA regulatory modules in epithelial-mesenchymal transition with a probabilistic topic model
TL;DR: Results on EMT data sets show that the inferred FMRMs can potentially construct the biological chain of 'miRNA→mRNA→condition' at the post-transcriptional level.