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The Data Mining and Machine Learning Group at the University of Houston aims at the development of data analysis and data management techniques with applications to challenging problems in physics, geology, astronomy, environmental sciences, and medicine. Areas of research include meta-learning, new classification algorithms, clustering, association analysis, distance function learning, spatial data mining, query optimization for statistical analysis and integration of machine learning techniques into a database system.
Statistics for Submissions in 2008: Dr. Eick, his collaborators, and students submitted 17 papers (14 conference, 2 journal, 1 workshop paper). 9 of these papers were accepted, 7 of the submitted papers were rejected, and one paper is still under review. Accepted and Submitted Papers in 2009: So far, 1 journal paper, 4 conference papers, 1 workshop paper, and 1 book chapter have been accepted; moreover, 2 conference papers and 3 journal papers are currently under review. |
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Copyright 2009: UH Data Mining and Machine Learning Group, Houston, TX |
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