Min Song

Min Song is an assistant professor of Department of Information Systems at NJIT. He received his M.S. in School of Information Science from Indiana University in 1996 and received Ph.D. degree in Information Systems from Drexel University in 2005. Min has a background in Text Mining, Bioinfomatics, Information Retrieval and Information Visualization.

Min received the Drexel Dissertation Award in 2005. In 2006, Min’s work received an honorable mention award in the 2006 Greater Philadelphia Bioinformatics Symposium. In addition, The paper entitled “Extracting and Mining Protein-protein interaction Network from Biomedical Literature” has received the best paper award from 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, which was held in San Diego, USA, Oct. 7-8, 2004. In addition, another paper entitled “Ontology-based Scalable and Portable Information Extraction System to Extract Biological Knowledge from Huge Collection of Biomedical Web Documents” was nominated as the best paper at 2004 IEEE/ACM Web Intelligence Conference, which was held in Beijing, China, Sept, 20-24, 2004.

Publications

International Journal of Computers in Clinical Practice (IJCCP)
Athina A. Lazakidou. Est. 2016.
The International Journal of Computers in Clinical Practice (IJCCP) provides comprehensive coverage on computational capabilities, models, and implementation for clinical...
Combining Supervised Learning Techniques to Key-Phrase Extraction for Biomedical Full-Text
Yanliang Qi, Min Song, Suk-Chung Yoon, Lori deVersterre. © 2013. 12 pages.
Key-phrase extraction plays a useful a role in research areas of Information Systems (IS) like digital libraries. Short metadata like key phrases are beneficial for searchers to...
A Comparative Study of an Unsupervised Word Sense Disambiguation Approach
Wei Xiong, Min Song, Lori deVersterre. © 2013. 11 pages.
Word sense disambiguation is the problem of selecting a sense for a word from a set of predefined possibilities. This is a significant problem in the biomedical domain where a...
A Comparative Study of an Unsupervised Word Sense Disambiguation Approach
Wei Xiong, Min Song, Lori deVersterre. © 2012. 11 pages.
Word sense disambiguation is the problem of selecting a sense for a word from a set of predefined possibilities. This is a significant problem in the biomedical domain where a...
Combining Supervised Learning Techniques to Key-Phrase Extraction for Biomedical Full-Text
Yanliang Qi, Min Song, Suk-Chung Yoon, Lori deVersterre. © 2011. 12 pages.
Key-phrase extraction plays a useful a role in research areas of Information Systems (IS) like digital libraries. Short metadata like key phrases are beneficial for searchers to...
A Dynamic and Semantically-Aware Technique for Document Clustering in Biomedical Literature
Min Song, Xiaohua Hu, Illhoi Yoo, Eric Koppel. © 2011. 13 pages.
As an unsupervised learning process, document clustering has been used to improve information retrieval performance by grouping similar documents and to help text mining...
International Journal of Computational Models and Algorithms in Medicine (IJCMAM)
. Est. 2010.
The International Journal of Computational Models and Algorithms in Medicine (IJCMAM) provides comprehensive coverage on computational capabilities, prototypes, and algorithms...
Handbook of Research on Text and Web Mining Technologies
Min Song, Yi-Fang Brook Wu. © 2009. 901 pages.
The massive daily overflow of electronic data to information seekers creates the need for better ways to digest and organize this information to make it understandable and...
Deep Web Mining through Web Services
Monica Maceli, Min Song. © 2009. 7 pages.
With the increase in Web-based databases and dynamically- generated Web pages, the concept of the “deep Web” has arisen. The deep Web refers to Web content that, while it may be...
Text Categorization
Megan Chenoweth, Min Song. © 2009. 6 pages.
Text categorization (TC) is a data mining technique for automatically classifying documents to one or more predefined categories. This paper will introduce the principles of TC...
A Dynamic and Semantically-Aware Technique for Document Clustering in Biomedical Literature
Min Song, Xiaohua Hu, Illhoi Yoo, Eric Koppel. © 2009. 14 pages.
As an unsupervised learning process, document clustering has been used to improve information retrieval performance by grouping similar documents and to help text mining...