5. The computer-implemented system according to claim 3 , wherein: when the position of the noun word Ki is not in a sentence, a determination is made as to whether or not the noun word Ki takes up the entire text segment; when the noun word Ki takes up the entire text segment, a score W is assigned to the noun word Ki; when the noun word Ki does not take up the entire text segment, a score Y is assigned to the noun word Ki; when the position of the noun word Ki is in a sentence, a determination is made as to whether or not the noun word Ki is in a parenthesis in the sentence and takes up the entire character string in the parenthesis; when the noun word Ki is in the parenthesis and takes up the entire character string in the parenthesis, a score X is assigned to the noun word Ki; and when the noun word Ki is not in a parenthesis or does not take up the entire character string, a score Z is assigned to the noun word Ki, wherein score W is greater than score X, score X is greater than score Y, and score Y is greater than score Z.
3. The computer-implemented system according to claim 1 , wherein: the first extraction unit uses the first text processing information to extract the noun word from the document data by performing a morphological analysis on the document data to extract noun words (Ki (i=1, 2 , . . . , n)); and the first extract unit further assigns, to each of the extracted noun words Ki, a weight corresponding to at least one of a position and a proportion of the noun word Ki in the document data.