Na Tang's Research
My research
focuses on applying web knowledge to the classification on insufficient
statistical data. Instead of using the traditional statistical methods on the incomplete
data, we explore methods to automatically retrieve web knowledge and methods to
further exploit the web knowledge for better classification. How to retrieve
the desired web documents, how to extract the desired knowledge from the
documents and how to combine the knowledge into classifiers with incomplete
data are the major challenge.
- N. Tang
and V. Rao Vemuri,
"Bayesian Inference by Combining Poor-quality Data with Knowledge. Submitted to
International Journal on Artificial Intelligence Tools (IJAIT).
2006. PDF
- N. Tang
and V. Rao Vemuri,
"
A Web-knowledge-based Clustering Model for Gene Expression Data Analysis. In
Proceedings of the 2006 Atlantic Web Intelligence Conference (AWIC06).
2006. PDF
- N. Tang
and V. Rao Vemuri,
"User-interest-based
Document Filtering via Semi-supervised Clustering. In
Proceedings of the 15th International Symposium on Methodologies for Intelligent
Systems (ISMIS 2005). Pages 573-582. 2005.
PDF
- N. Tang
and V. Rao Vemuri,
"An Artificial Immune System Approach to Document Clustering,"
In Proceedings of the 20th ACM Symposium on Applied Computing (SAC2005), Evolutionary
Computing and Optimization (EC) Track. Pages 918 - 922. 2005.PDF
- Na Tang
and V. Rao Vemuri,
"Web-based Knowledge Acquisition to Impute Missing Values for
Classification," In Proceedings of the 2004 IEEE/WIC/ACM International Joint Conference on
Web Intelligence. Pages 124-130. Sep. 20-24, 2004. Beijing, China.
PDF
- V. Rao Vemuri and N. Tang, “Solving Inverse Problems via Machine Learning
and Knowledge Discovery," in (Eds. Takumi Ichimura
and Katsumi Yoshida.), Knowledge-Based Intelligent Systems for
Healthcare, CRC Press, 2004. PDF