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 social science.