BACKGROUND OF TECHNOLOGY

Some computing devices may store large records of data associated with one or more entities. Classifying such entities into categories can sometimes be an inaccurate, resource intensive, and complex problem.

SUMMARY OF DESCRIBED SUBJECT MATTER

In some embodiments, the present disclosure provides a technically improved computer-based system/method/apparatus that includes at least the following components/steps of an entity classification system that receives informational data associated with an entity. The informational data can include sentences associated with the entity. The entity classification system can utilize a first machine learning model to determine a first contextual meaning among words of a sentence associated with the entity based on a first word embedding technique, and determines at least one category associated with the entity based at least in part on the first contextual meaning. The entity classification system can utilize a second machine learning model to determine a second contextual meaning shared by a set of sentences based on a second embedding technique, and determines a subcategory of the category associated with the entity based at least in part on the second contextual meaning. The entity classification system generates an output including the category and subcategory associated with the entity.

In some embodiments, the first machine learning model can produce a set of category profiles represented by word embeddings, and a category associated with an entity is determined at least in part on a category profile represented by word embeddings from the set of category profiles represented by word embeddings.

In some embodiments, the second machine learning model can produce a set of subcategory profiles represented by word embeddings, and the subcategory associated with the entity is determined at least in part on a subcategory profile represented by word embeddings from the set of subcategory profiles represented by word embeddings.

In some embodiments, the entity classification system determines a category associated with an entity and the subcategory associated with the entity at least in part utilizing a cosine similarity technique between information data associated with the entity and, a set of category profiles represented by word embeddings or a set of subcategory profiles represented by word embeddings. For computing cosine similarity, the words appearing for the entity is being replaced by corresponding word embeddings obtained for the category it being matched.

