Abstract: The present disclosure relates to dynamically merging database tables according to user specified parameters. A user may specify a threshold confidence level that relates to a likelihood that two database records represent the same real-world entity. In addition, a user may specify a merge rule such as desired fields or a manner for consolidating the variations of the information in desired fields from the related records. The original database tables are preserved so that users can iteratively create new dynamically merged database tables by varying the parameters.
Type:
Grant
Filed:
October 11, 2017
Date of Patent:
March 24, 2020
Assignee:
Amperity, Inc.
Inventors:
Derek Slager, Stephen Meyles, Yan Yan, Carlos Sakoda
Abstract: The present disclosure relates to evaluating whether two data records reflect the same entity using a classifier in the absence of ground truth. Without ground truth, it is difficult to determine the precision or recall of a classifier. The present disclosure generates output data comprising a list of unique signatures generated from a set of records that are compared with each other. The output data may also comprise corresponding record pairs limited to a predetermined sample size for each unique feature signature.
Type:
Grant
Filed:
October 11, 2017
Date of Patent:
December 17, 2019
Assignee:
Amperity, Inc.
Inventors:
Yan Yan, Stephen Meyles, Mona Akmal, Michael P. Fikes