Abstract
The second component of data integration is record linkage. Even after the schemas of different sources have been aligned, when different sources provide values for the same attribute of the same entity, these values may differ due to mis-typing, multiple naming conventions, and so on. To illustrate, in our Flights example in Chapter 1, flight numbers are represented in source Airline2 using digits (e.g., 53 in r32), while they are represented in source Airfare4 using alphanumerics (e.g., A2-53 in r32). Similarly, airports are represented in source Airline2 using 3-letter codes (e.g., EWR and SFO in r32), but as descriptive strings in Airfare4.Flight (e.g., Newark Liberty and San Francisco in r64). These representational differences make it hard to link records r32 and r64, even though they refer to the same entity. The goal of record linkage is to decide which records refer to the same entity, and which refer to different entities.
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Dong, X.L., Srivastava, D. (2015). Record Linkage. In: Big Data Integration. Synthesis Lectures on Data Management. Springer, Cham. https://doi.org/10.1007/978-3-031-01853-4_3
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DOI: https://doi.org/10.1007/978-3-031-01853-4_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-00725-5
Online ISBN: 978-3-031-01853-4
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