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Workshop on Data Mining Methodology and Applications
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Data mining is a new and fast-changing discipline, which aims at the discovery of unusual and unexpected patterns in large volumes of data.It came to life in response to the challenges and opportunities provided by the increasing number of very large high-dimensional data bases covering important areas of human activity, such as industrial, economical, social and biomedical developments. Data mining borrows from several long-established disciplines, among them, data base technology, machine learning and statistics. The workshop will focus on the interplay of statistics and data mining. Statistical learning theory provides the foundation for learning from data in the presence of uncertainty. At the same time, typical problems of data mining spur statistical research into new directions. The workshop will contain a mix of sessions on both data mining methodology and real-world applications and problems. Participants and speakers will include both academics and practical data miners, and include perspectives from statistics, machine learning, marketing, and other related disciplines. Topics will include both supervised and unsupervised learning, and the ``rare target'' problem, in which the goal is to identify classes or groups of data that are exceedingly uncommon but highly valuable. The format of the workshop will include talks, panel discussions, and open discussion sessions, with a view towards stimulating interactions between participants and identification of promising new directions in research and applications. Graduate students are encouraged to participate, and may apply for limited travel funding. Invited speakers: (titles and abstracts)
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