Groupon, Inc.

Bytedance Inc.

Taylor Raack

David Alan Johnston

Matthew DeLand

Shawn Ryan Jeffrey

Shawn Jeffrey

Systems, apparatus, and methods for determining unique contacts from a collection or pool of merchant data are discussed herein. Some embodiments may provide for an apparatus including circuitry configured to determine programmatic match results indicating whether different instances of merchant data match (e.g., describe the same contact). The circuitry may further determine probabilities of precision or recall errors with the programmatic match results. Programmatic match results having a high probability of error may be annotated by a user to generate user match results. The user match results may be used to generate a more reliable contacts database including unique contacts, as well as to train and/or update the match scoring algorithm. As such, the accuracy of machine-implemented binary classification is improved.

Systems, apparatus, and methods of programmatically determining unique contacts based on crowdsourced error correction

In general, embodiments of the present invention provide systems, methods and computer readable media for automatic cleaning of entity resolution (ER) data persistently stored in a data repository.

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Chicago, IL, United States of America

Taylor Raack