Method and device for identifying machine learning models for detecting entities

An entity identification device for identifying a machine learning model for detecting entities from data, the entity identification device comprising:

• a processor;
• and
• a memory communicatively coupled to the processor, wherein the memory stores processor instructions, which, on execution, causes the processor to:
• identify a first entity from within data, wherein a machine learning model trained to identify the first entity is absent in a plurality of machine learning models, wherein each of the plurality of machine learning models is trained to identify at least one entity from a set of second entities;
• extract a first set of entity attributes associated with the entity;
• match the first set of entity attributes with each of a plurality of second set of entity attributes extracted for the set of second entities;
• identify a second entity from the set of second entities based on the matching, wherein similarity between a second set of entity attributes associated with the second entity and the first set of entity attributes is above a similarity threshold;
• and
• retrain a machine learning model associated with the second entity to identify the first entity based on the first set of entity attributes.

A non-transitory computer-readable storage medium comprising a set of computer-executable instructions causing a computer comprising one or more processors to perform steps comprising:

• identifying a first entity from within data, wherein a machine learning model trained to identify the first entity is absent in a plurality of machine learning models, wherein each of the plurality of machine learning models is trained to identify at least one entity from a set of second entities;
• extracting a first set of entity attributes associated with the entity;
• matching the first set of entity attributes with each of a plurality of second set of entity attributes extracted for the set of second entities;
• identifying a second entity from the set of second entities based on the matching, wherein similarity between a second set of entity attributes associated with the second entity and the first set of entity attributes is above a similarity threshold;
• and
• retraining a machine learning model associated with the second entity to identify the first entity based on the first set of entity attributes.