Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, pattern discovery, and association analysis) Models and algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains Developing a unifying theory of data mining Mining sequences and sequential data Mining spatial and temporal datasets Mining textual and unstructured datasets Distributed data mining High performance implementations of data mining algorithms Privacy- and anonymity-preserving data analysis