Abstract
As companies gather and process more data from disparate sources, they are relying more heavily on entity resolution. Currently, creating an entity resolution system is a very procedural process. Blocking, transitive closure, and matching must all be pieced together whether by an Extract, Transform, and Load (ETL) tool or by a custom program (Galhardas et al. 2000). This is similar to the state of data querying before the advent of the Structured Query Language (SQL). In this chapter, a declarative approach to entity resolution is presented that gives the user the ability to specify what he or she would like resolved while allowing a code generator to determine the best way to resolve it. This chapter does not explore algorithms for blocking, transitive closure, clustering, or matching, but instead refers to papers on those subjects written by other authors (Baxter et al. 2003; Gu and Baxter 2004; Winkler 2000, 2003; Jaro 1989; Bhattacharya and Getoor 2006). Instead a background and defense of entity resolution and declarative languages is presented with a declarative solution and a possible representation.
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Gibbs, T.H. (2009). A Declarative Approach to Entity Resolution. In: Chan, Y., Talburt, J., Talley, T. (eds) Data Engineering. International Series in Operations Research & Management Science, vol 132. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0176-7_2
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