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Wednesday, February 23, 2000

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AAAI 2000 Workshop Learning Statistical Models From Relational Data
"Researchers from a variety of backgrounds (including machine learning, statistics, inductive logic programming, databases, and reasoning under uncertainty) are beginning to develop techniques to learn statistical models from relational data. This work diverges from traditional approaches in these fields that assume data instances are structurally identical and statistically independent or assume that relationships are deterministic. New developments in this area are vital because of the growing interest in mining information in relational databases, object-oriented databases, XML and other structured and semi-structured formats. The workshop will focus on learning models that represent statistical correlations between the properties of related entities directly from relational data."

[ rhetoric ]

Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.


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