Encyclopedia of Big Data

Living Edition
| Editors: Laurie A. Schintler, Connie L. McNeely

Link/Graph Mining

  • Derek Doran
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-32001-4_129-1



Link/graph mining is defined as the extraction of information within a collection of interrelated objects. Whereas conventional data mining imagines a database as a collection of “flat” tables, where entities are rows and attributes of these entities are columns, link/graph mining imagines entities as nodes or vertices in a network, with attributes attached to the nodes themselves. Relationships among datums in a “flat” database may be seen by primary key relationships or by common values across a set of attributes. In the link/graph mining view of a database, these relationships are made explicit by defining links or edges between vertices. The edges may be homogeneous, where a single kind of relationship defines the edges that are formed, or heterogeneous, where multiple kinds of data are used to develop a vertex set, and relationships define edges among network vertices. For example, a...

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Further Readings

  1. Cook, D. J., & Holder, L. B. (2006). Mining graph data. Wiley.Google Scholar
  2. Getoor, L., & Diehl, C. P. (2005). Link mining: A survey. ACM SIGKDD Explorations Newsletter, 7(2), 3–12.CrossRefGoogle Scholar
  3. Lewis, T. G. (2011). Network science: Theory and applications. Wiley.Google Scholar
  4. Newman, M. (2010). Networks: An introduction. New York: Oxford University Press.Google Scholar
  5. Philip, S. Y., Han, J., & Faloutsos, C. (2010). Link mining: Models, algorithms, and applications. Berlin: Springer.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringWright State UniversityDaytonUSA