Learning Structure From Statistical Models

TitleLearning Structure From Statistical Models
Publication TypeJournal Articles
Year of Publication2003
AuthorsGetoor L
JournalIEEE Data Engineering Bulletin
Volume26
Issue3
Pagination11 - 18
Date Published2003///
Abstract

Statistical relational learning is a newly emerging area of machine learning that combines statisticalmodeling with relational representations. Here we argue that it provides a unified framework for the
discovery of structural information that can be exploited by a data management system. The categories
of structure that can be discovered include: instance-level dependencies and correlations, for example
intra-table column dependencies and inter-table join dependencies; record linkages and duplicates; and
schema matching and schema discovery from unstructured and semi-structured data.