Co-directed by:
Mission Statement
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.
One area of research is the development of a tool for the automated
and/or semi-automated analysis and characterization of Martian
topography; the tool produces thematic maps of the topography for
localized regions on Mars that are of special interest to domain
experts. Other work centers on the discovery of interesting regions
in spatial data sets, and the application of those techniques
to challenging problems in environmental risk assessment and in
geology. Another piece of work is centered on the identification of
particle physics by analyzing huge data sets provided by current
particle accelerators. Other research focuses on how to adapt input
parameters of data mining algorithms based on feedback, and on the
development of scalable clustering algorithms.
