2. The computer-assisted method of claim 1 , wherein each of the text units is a sentence or a paragraph.
1. A computer-assisted method for discovering topics in a document, comprising: obtaining a first group of text units in a first document by a computer system, each of the text units in the first group comprises one or more words; tokenizing the first group of text units by the computer system to produce a plurality of tokens that include a jth token; assigning token types to the tokens in the first group of text units according to the grammatical roles of the tokens; assigning weighting coefficients to the tokens in the first group of text units according to the token types of the tokens; for each text unit in the first group that includes the jth token, adding a weighting coefficient to a parameter token_j_count; dividing a cumulative value of the parameter token_j_count obtained from the first group of text units by the total number of text units in the first group to produce an internal term prominence (ITP) value for the jth token; calculating a term prominence value for the jth token using at least the ITP value of the jth token; selecting one or more tokens from the plurality of tokens at least in part based on the term prominence values of the respective tokens; and outputting, by the computer system, one or more topic terms comprising the selected one or more tokens to represent the topics in the first document.