Machine Learning To Tune Probabilistic Matching In Entity Resolution Systems

A computer program product comprising one or more computer-readable storage media collectively containing computer-readable program code that, when executed by operation of one or more computer processors, performs an operation comprising:

• receiving a plurality of data records;
• generating a first comparison vector by comparing a first and a second data record of the plurality of data records, wherein the first comparison vector indicates differences between the first and second data records;
• training a machine learning model based at least in part on the first comparison vector;
• evaluating the plurality of data records using the machine learning model;
• and
• linking at least two of the plurality of data records based on the evaluation.

A system comprising:

• one or more computer processors;
• and
• one or more memories collectively containing one or more programs which when executed by the one or more computer processors performs an operation, the operation comprising:
• receiving a plurality of data records;
• generating a first comparison vector by comparing a first and a second data record of the plurality of data records, wherein the first comparison vector indicates differences between the first and second data records;
• training a machine learning model based at least in part on the first comparison vector;
• evaluating the plurality of data records using the machine learning model;
• and
• linking at least two of the plurality of data records based on the evaluation.