Introduction to the special issue on link mining

  • Authors:
  • Lise Getoor;Christopher P. Diehl

  • Affiliations:
  • University of Maryland, College Park, MD;Johns Hopkins University, Laurel, MD

  • Venue:
  • ACM SIGKDD Explorations Newsletter
  • Year:
  • 2005

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Abstract

An emerging challenge for data mining is the problem of mining richly structured datasets, where the objects are linked in some way. Many real-world datasets describe a variety of entity types linked via multiple types of relations. These links provide additional context that can be helpful for many data mining tasks. Yet multi-relational data violates the traditional assumption of independent, identically distributed data instances that provides the basis for many statistical machine learning algorithms. Therefore, new approaches are needed that can exploit the dependencies across the attribute and link structure.