Methods, systems, and computer readable media for utilizing machine learning for merging duplicate data records

A system comprising:

• at least one processor;
• a memory element;
• a data record consolidation (DRC) manager stored in the memory element and when executed by the at least one processor is configured for receiving a plurality of duplicate data records, constructing a plurality of collection level feature attributes from the duplicate data records, extracting one or more samples from the plurality of collection level feature attributes, and receiving domain expert stimulus input corresponding to the one or more samples;
• and
• a merging machine learning (MML) model stored in the memory element and when executed by the at least one processor is configured for utilizing the merging machine learning model to generate a master data record corresponding to the duplicate data records or a rule to derive the master data record, wherein the merging machine learning model is trained by the DRC manager using the stimulus input.

A non-transitory computer readable medium having stored thereon executable instructions that when executed by at least one processor of a computer cause the computer to perform steps comprising:

• receiving a plurality of duplicate data records;
• constructing a plurality of collection level feature attributes from the duplicate data records;
• extracting one or more samples from the plurality of collection level feature attributes;
• receiving domain expert stimulus input corresponding to the one or more samples;
• training a merging machine learning model using the stimulus input;
• and
• utilizing the merging machine learning model to generate a master data record corresponding to the duplicate data records or a rule to derive the master data record.