SYSTEMS AND METHODS FOR TRAINING AND USING A MACHINE-LEARNING MODEL FOR DETERMINING THE SIMILARITY OF ENTITIES

There are many situations in which it is useful to identify similar entities or to quantify how similar one entity is to another. However, similarity is often subjective, making it challenging to determine the similarity of two entities computationally. In order to allow for determining the similarity of entities according to a customizable definition of similarity, a selection of features for determining similarity is received from a user device and a machine-learning model is trained to encode the values of the selected features for a particular entity as a representation. The representations of two different entities may be compared to determine the similarity of the two entities according to the selected features. The trained machine-learning model may, additionally or alternatively, be used for cluster analysis to identify similar groups of entities.