Artificial Intelligence Classification Model for Modern Chinese Poetry in Education

Various modern Chinese poetry styles have influenced the development of new poetry; therefore, classification style is very important for understanding these poems and promoting education regarding poetry. For learners, due to a lack experience, it difficult accurately judge poetry, which makes learners understand researchers, in mainly carried out by experts, there are some disputes between them, leads incorrect subjective To solve problems eXtreme Gradient Boosting (XGBoost) algorithm used this paper build an automatic model can automatically objectively classify First, divided into words, stopwords removed. Then, Doc2Vec obtain vector each poem. The was iteratively trained using XGBoost, iteration promotes optimization next generation until obtained, named Modern Poetry based on XGBoost (XGBoost-MCP). Finally, XGBoost-MCP built experiments real datasets compared with Support Vector Machine (SVM), Deep Neural Network (DNN), Decision Tree (DT) models. experimental results show that performs above 90% all data evaluations, obviously superior other three algorithms, has high accuracy objectivity. Applying help researchers better study