My research interests focus on data/text mining
and machine learning techniques for knowledge
discovery. Specifically, my research has covered
several applications areas of knowledge discovery,
such as bioinformatics, security, business, science and
engineering literature. I have been investigating
the analysis and modeling of data and information
of different types in these areas, including structured
data (e.g., numeric data and relational data from
databases) and unstructured data (e.g., literature
articles and online messages). Methodological
foundation for my research is from several disciplines
including machine learning, statistics, and computational
linguistics theory.
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BIOINFORMATICS |
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Learning gene regulatory
network from microarray data
- Z. Huang, J. Li, H. Su, G.S.
Watts, H. Chen, “Large-scale Regulatory
Network Analysis From Microarray Data:
Modified Bayesian Network Learning and
Association Rule Mining,” Decision
Support Systems (DSS), in
press.
- G. Leroy, H. Chen, J. Martinez, S. Eggers,
R. Falsey, K. Kislin, Z. Huang, J.
Li, J. Xu, D. McDonald, and G. Ng.
“Genescene: Biomedical Text and
Data Mining,” the Third ACM/IEEE
Joint Conference on Digital Libraries,
Houston, Texas, May 27-31, (2003).
Gene selection from
microarray-based for cancer classification
- J. Li, H. Su, H. Chen, B. Futscher,
“Optimal Search-Based Gene Subset
Selection for Gene Array Cancer Classification,”
IEEE Transactions on Information Technology
in Biomedicine (IEEE-TITB),
forthcoming.
- J. Li, H. Su, H. Chen, B. Futscher,
“Optimal Search-based Gene Subset
Selection: An Experiment on Ovarian Cancer
Survival Prediction,” under review
at Journal of the American Medical
Informatics Association (JAMIA).
- J. Li, H. Su, H. Chen, “Identification
of Marker Genes from High-dimensional
Microarray Data for Cancer Classification,”
in Y. Pan and X. Hu (Eds.), “Knowledge
Discovery in Bioinformatics: Techniques,
Methods and Applications,” forthcoming.
- J. Li, H. Hua, H. Chen, “Optimal
Search-based Gene Selection for Cancer
Diagnosis,” the Eleventh
Annual Americas Conference on Information
Systems (AMCIS’05), Omaha,
Nebraska, August 11-14, (2005).
Information extraction from biomedical literature text
- J. Li, Z. Zhang, X. Li, H. Chen, "Kernel-based Learning for Biomedical Relation Extraction," Journal of the American Society for Information Science and Technology (JASIST), forthcoming.
Integration of gene
functional relations from multiple resources
- J. Li, X. Li, H. Su, H. Chen,
D.W. Galbraith, “A Framework of
Integrating Gene Functional Relations
from Heterogeneous Data Sources: an Experiment
on Arabidopsis thaliana,” Bioinformatics,
22(16):2037-2043, (2006).
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BUSINESS |
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Business process mining from policy documents
- J. Li, H. J. Wang, Z. Zhang, J. L. Zhao, "Mining Business Policy Texts for Discovering Process Models: A Framework and Some Initial Results," the 6 th Workshop on e-Business (WeB 2007), Montreal, Quebec, Canada, December 9, 2007 (Best Paper Award Nominee).
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SECURITY |
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Automatic authorship analysis for cybercrime investigation
- J. Li, R. Zheng, H. Chen, “From Fingerprint to Writeprint,” Communications of the ACM (CACM), 49(4), 76-82, (2006).
- R. Zheng, J. Li, H. Chen, Z. Huang, Q. Yi, “A Framework of Authorship Identification for Online Messages: Writing Style Features and Classification Techniques,” Journal of the American Society for Information Science and Technology (JASIST), 57(3), 378-393, (2006).
Identity matching in law enforcement databases
- J. Xu, G. Wang, J. Li, M. Chau, “Complex Problem Solving: A Case Study on Identity Matching Based on Social Contextual Information,” JAIS Special Issue Enid Mumford’s Contribution to Information Systems Theory and Theoretical Thinking, forthcoming
- J. Li, G. Wang, H. Chen, “Identity Matching Based on Probabilistic Relational Models,” the Twelfth Americas Conference on Information Systems (AMCIS’06), Acapulco, México, August 4-6, (2006).
- “Identity Matching Based on Probabilistic Relational Models,” with G. Alan Wang, Hsinchun Chen, targeted at Information Systems Research.
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SCIENCE &
ENGINEERING LITERATURE |
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Automated patent classification
- X. Li, H. Chen, Z. Zhang, J. Li, "Auto Patent Classification Using Citation Network Information: An Experimental Study in Nanotechnology," ACM IEEE Joint Conference on Digital Libraries (JCDL), Vancouver, British Columbia, Canada, 2007.
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