Data Mining in the Presence of Quantitatively and Qualitatively Diverse Information

IDM-0415190

Anne M. Denton <anne.denton@ndsu.edu>

North Dakota State University

Grant Homepage http://www.cs.ndsu.nodak.edu/~adenton/IDM/
PI Homepage: http://www.cs.ndsu.nodak.edu/~adenton/
Abstract

Findings

Project Pages

Graph-Relational Data Mining

Length-Dependent Sequence Clustering

Journal Publications

• Anne M. Denton and Jianfei Wu, “Data mining of vector-item patterns using neighborhood histograms,” Knowledge and Information Systems (KAIS) journal, (in press). (online access)
• Dietmar H. Dorr, Anne M. Denton, "Generalised sequence signatures through symbolic clustering," International Journal of Data Mining and Bioinformatics, (in press).
  
• Dietmar H. Dorr, Anne M. Denton, "Clustering sequences by overlap," International Journal of Data Mining and Bioinformatics, 3(3):260-279, 2009. (online access)
• Dietmar H. Dorr and Anne M. Denton, “Establishing relationships among patterns in stock market data,” Data & Knowledge Engineering, 68(3):318-337, March 2009. (online access)
  
• Anne Denton, "Subspace sums for extracting non-random data from massive noise," Knowledge and Information Systems (KAIS) journal 20(1):35-62, July 2009. (online access)
  
• Anne M. Denton, Christopher A. Besemann and Dietmar H. Dorr, "Pattern-based time-series subsequence clustering using radial distribution functions," Knowledge and Information Systems (KAIS) journal, 18(1):1-27, January 2009. (online access)
• Anne M. Denton, Jianfei Wu, Megan K. Townsend, Preeti Sule, and Birgit M. Prüß,“Relating gene expression data on two-component systems to functional annotations in Escherichia coli,” BMC Bioinformatics, 9:294, 2008. (online access)
  
• Christopher Besemann, Anne Denton, Nathan J Carr and Birgit M Pruess, "BISON: bio-interface for the semi-global analysis of network patterns," Source Code for Biology and Medicine, 1:8, 2006. (online access)
• Birgit M. Prüβ, Christopher Besemann, Anne Denton, and Alan J. Wolfe, "A complex transcription network controls the early stages of biofilm formation," J. Bacteriol. 188:3731-3739, 2006.

Conference and Workshop Publications

• Jianfei Wu, Anne M. Denton, Omar El-Ariss, and Dianxiang Xu, "Mining core patterns in stock market data," Mining Multiple Information Sources Workshop in conjunction with the 2009 IEEE International Conference on Data Mining, Miami, Dec 6, 2009.
• Dietmar Dorr and Anne Denton, "A pattern mining approach toward discovering generalized sequence signatures," SIAM International Conference on Data Mining (SDM08), Atlanta, GA, April 24-26, 2008. (online access)
• Dietmar Dorr and Anne Denton, "Generalized sequence signatures through symbolic clustering," Workshop on Machine Learning in Biomedicine and Bioinformatics in conjunction with the Sixth International Conference on Machine Learning and Applications, Cincinnati, OH, Dec. 13-15, 2007. (online access)
  
• Jianfei Wu and Anne Denton, " Mining vector-item patterns for annotating protein domains," Mining Multiple Information Sources Workshop in conjunction with the ACM KDD '07 Conference on Knowledge Discovery and Data Mining, San Jose, CA, Aug. 12, 2007, ISBN: 978-1-59593-840-4. (online access)
• Anne Denton and Angshu Kar, "Finding differentially expressed genes through noise elimination," Workshop on Data Mining for Biomedical Informatics in conjunction with the Sixth SIAM International Conference on Data Mining, Minneapolis, MN, April 28, 2007. 
• Christopher Besemann and Anne Denton, "Mining edge-disjoint patterns in graph-relational data," Workshop on Data Mining for Biomedical Informatics in conjunction with the Sixth SIAM International Conference on Data Mining, Minneapolis, MN, April 28, 2007. 
• Anne Denton, "Kernel-density-based clustering of time series subsequences using a continuous random-walk noise model," In Proceedings The Fifth IEEE International Conference on Data Mining (ICDM'05), Houston, Texas, Nov. 27-30, 2005. (online access)
  
  

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This material is based upon work supported by the National Science Foundation under Grant No. IDM-0415190.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.