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Learning statistical models from relational data

Published:12 June 2011Publication History

ABSTRACT

Statistical Relational Learning (SRL) is a subarea of machine learning which combines elements from statistical and probabilistic modeling with languages which support structured data representations. In this survey, we will: 1) provide an introduction to SRL, 2) describe some of the distinguishing characteristics of SRL systems, including relational feature construction and collective classification, 3) describe three SRL systems in detail, 4) discuss applications of SRL techniques to important data management problems such as entity resolution, selectivity estimation, and information integration, and 5) discuss connections between SRL methods and existing database research such as probabilistic databases.

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    • Published in

      cover image ACM Conferences
      SIGMOD '11: Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
      June 2011
      1364 pages
      ISBN:9781450306614
      DOI:10.1145/1989323

      Copyright © 2011 ACM

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      Publication History

      • Published: 12 June 2011

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