Abstract: This paper extracted high-frequency keywords appearing in the literature, then positioned the abstract through inverted index, mined the fixed semantic phrases with keywords in the abstract, and tracked the dynamic chan- ges phrases in recent years by text bibliometric. 13y using the related affect matrix to establish associated network, the association between the semantic phrases was analysed and figured out. The experimental results show that the litera- lure summary implicit knowledge fragments can better reflect the trends of disciplines.

Key words: Inverted index, Next bibliometric, Related affect matrix, Social network analysis