This chapter presents three models of ER. The models are complementary in that they address different levels and aspects of the ER process. The first and earliest model discussed is the Fellegi-Sunter Model, a methodology for linking equivalent references by direct matching. The Fellegi-Sunter Model provides a specific algorithm for of resolving pairs of references through probabilistic matching. The second model is the Stanford Entity Resolution Framework (SERF), which defines a generic model of ER in terms of matching and merging operations that act on pairs of references. Unlike Fellegi-Sunter, the SERF model does not define a specific implementation for the match (or merge) operation but instead focuses on methods for resolving a large set of references by the systematic application of the pairwise operations. The third is the Algebraic Model, which describes ER from an even higher level of abstraction. It focuses on the outcome of the ER process and on metrics for comparing the outcomes of different ER processes acting on the same set of references. The Algebraic Model views an ER process as defining an equivalence relation on a set of references. The Algebraic Model extends beyond the ER process to include a model for entity-based data integration (EBDI), discussed in more detail in Chapter 4…
[MK] Andrea
