The invention provides a fine-grained text classification method based on capsule network masked memory attention, which is a method for classifying emotional tendency of a subjective text on an object or a certain aspect of the object according to the subjective comment text published by a user on the object or the certain aspect of the object and keywords or key phrases of the object or the certain aspect of the object. According to the fine-grained text classification method based on the capsule network mask memory attention, the purposes of improving the complex text modeling capability of a model and improving the adaptability of the model to different complexity tasks can be achieved.
Fine-grained text classification method based on capsule network mask memory attention