Knowledge Base Processing Method Based on Text Classification Algorithm

The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. In practical application, the knowledge base processing method has been prove to have a good performance in text classification tasks. The utilization of knowledge base processing method in text classification has led to an average accuracy improvement of more than 17%. Furthermore, this method significantly reduces labeling costs by approximately 70% compared to traditional approaches. Recently, knowledge base processing methods have been widely used in supporting business applications, social media analysis and other fields. This paper proposes a knowledge base method to establish a feature model related to domain speciality and combine it with traditional text classification algorithm, so as to optimize the training and reasoning process of the classification model and improve the accuracy of classification effect. Lastly, we suggested strategies to overcome the shortcoming of the knowledge base method in improving the construction and training of the classification model.