TEXT CLASSIFICATION WITH WEIGHTED EMBEDDINGS

Original (Chinese)

Aspects of the present disclosure relate to automated transaction categorization. Embodiments include generating, via an embedding model, a first embedding representation of a training text; assigning, via a text classification model, a class to the training text based on the first embedding representation of the training text; generating an embedding representation of a given phrase within the training text based on confirming that the class assigned to the training text is an incorrect class for the training text, wherein the given phrase is selected based on an association between the given phrase and a correct class for the training text; generating an updated embedding representation of the training text based on the first embedding representation of the training text and the embedding representation of the given phrase; and training the text classification model through a supervised learning process involving the updated embedding representation of the training text.