Abstract: Based on the fundamental goal of digging out the literary connotation of common plants,this research aims to visualize the connection between plants and literature. We construct a topic model to explore the affiliation and relevance of literarily images of plants and present the correspondence of term and theme with two network diagrams. This study uses the LDA topic model to process the distribution of 7 topics among 35 kinds of trees and analyzes the relationship between the topics and the related terms.The results obtained show an excellent classification effect,further revealing the close relationship between the cultural connotations of different plants and realizing the application of text mining to interpret plant-centered literary intentions.

Key words: plants, Literature, text classification, LDA topic model, visualization