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...
- Cook, D. J., & Holder, L. B. (2006). Mining graph data. Wiley.Google Scholar
- Lewis, T. G. (2011). Network science: Theory and applications. Wiley.Google Scholar
- Newman, M. (2010). Networks: An introduction. New York: Oxford University Press.Google Scholar
- Philip, S. Y., Han, J., & Faloutsos, C. (2010). Link mining: Models, algorithms, and applications. Berlin: Springer.Google Scholar