Learning Statistical Models from Relational Data
Papers from the AAAI Workshop
Lise Getoor and David Jensen, Cochairs
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 focused on learning models that represent statistical correlations between the properties of related entities directly from relational data.