The invention relates to a topic phrase extraction method. The topic phrase extraction method includes preprocessing documents, seeking a document-topic set, a full text lexical chain set and a noun phrase set, seeking a central word set, seeking a candidate topic phrase set, and seeking a topic phrase set. The topic phrase extraction method has the advantages that topic phrases are extracted through combination between an LDA (latent Dirichlet allocation) model and a lexical chain, a knowledge base WordNet with complete semantic information outside a corpus can be utilized, a strong lexical chain can be acquired through semantic relevance calculation and strong chain rule filtration, and accordingly, the ambiguity of topic words is reduced greatly; the topic phrases are extracted according a central word extraction method and by N-P rule combination and deduplication steps, and topics are expressed by the topic phrases with rich semantic information, so that the problems such as low granularity and recognition degree of the topic words are solved, topic extraction accuracy and recall rate can be guaranteed, topic drifting is reduced, and needs of practical applications can be wellmet.