Database Matching Algorithm

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Advanced algorithms for record matching and entity resolution.,Data matching is the process of identifying which records from data sources correspond to the same real-world entity.,Each data matching domain has special challenges when trying to match records from different sources to the real-world entity or object.,Probabilistic matching algorithms rely on statistical techniques for assessing the probability that any pair of records represent the same entity.

Record matching activities are inherently quadratic. Notionally, all records from one data set need to be compared with all records from the other data set, so the total number of comparison is the product of the sizes of the two data sets. For large data sets, the notional number of comparisons can be extremely large.

In practice, all record matching techniques involve an indexing stage designed to reduce the number of comparisons. For equality-based matching, the matching logic can be stated in terms of JOIN and WHERE clauses, which allows the database query analyser to apply database indexing to linearize the comparison complexity. For pairwise comparison, a database query analyser cannot apply indexing to linearize the the comparison complexity. Instead, pairwise comparison uses other indexing techniques to reduce the number of comparisons.

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