Systems and methods for human-in-the-loop training of a machine learning model for extracting targets from records

A system for training a machine learning model by extracting one or more targets from records, the system comprising:

• a memory storing instructions;
• and
• a processor operatively connected to the memory and configured to execute the instructions to perform operations including:
• receiving data packets including data associated with previous interactions of a first user;
• determining at least one party to the previous interactions with whom the first user interacted at a level above a threshold;
• comparing the at least one party to a plurality of parties identified in a target database to identify at least one potential target;
• for each of the at least one potential targets, determining a respective target metric by inputting the data packets into a machine learning model;
• providing an identification of the at least one potential target, with reference to the respective target metrics, to a user device associated with the first user;
• receiving, via the user device, feedback regarding the identification;
• and
• training the machine learning model based on the feedback.

A non-transitory computer readable medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform operations for training a machine learning model by extracting one or more targets from records, the operations comprising:

• receiving data packets including data associated with previous interactions of a first user;
• determining at least one party to the previous interactions with whom the first user interacted at a level above a threshold;
• comparing the at least one party to a plurality of parties identified in a target database to identify at least one potential target;
• for each of the at least one potential targets, determining a respective target metric by inputting the data packets into a machine learning model;
• providing an identification of the at least one potential target, with reference to the respective target metrics, to a user device associated with the first user;
• receiving, via the user device, feedback regarding the identification;
• training the machine learning model based on the feedback;
• providing the at least one potential target to a second user device associated with a second user;
• receiving an indication from the second user device that the second user has visited a website associated with the at least one potential target;
• and
• further training the machine learning model based on the indication.