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Record linkage, or computer matching, is needed for the creation and maintenance of name and
address lists that support operations for and evaluations of a Year 2000 Census. This paper describes
three advances. The first is an enhanced method of string comparison for dealing with typographical
variations and scanning errors. It improves upon string comparators in computer science. The second
is a linear assignment algorithm that can use only 0.002 as much storage as existing algorithms in
operations research, requires at most an additional 0.03 increase in time, and has less of a tendency
to make erroneous matching assignments than existing sparse-array algorithms because of how it
deals with most arcs. The third is an expectation-maximization algorithm for estimating parameters in
latent class, loglinear models of the type arising in record linkage. The associated theory and software
are the only known means of dealing with general interaction patterns and allow weak use of a priori
information via a generalization to the MCECM algorithm of Meng and Rubin. Models assuming that
interactions are conditionally independent given the class are typically considered in biostatistics and