3. The document clustering system according to claim 2 , wherein the concept similarity computation unit finds the concept similarity based on the ratio of the frequency of appearance in the document set of higher-order words or words of a subordinate category of the higher-order words that are common to the two words in the concept tree structure with respect to the frequency of appearance in the document set of each of the two words, or based on the amount of information.
3. The document clustering system according to claim 2 , wherein the concept similarity computation unit finds the concept similarity based on the ratio of the frequency of appearance in the document set of higher-order words or words of a subordinate category of the higher-order words that are common to the two words in the concept tree structure with respect to the frequency of appearance in the document set of each of the two words, or based on the amount of information. 4. The document clustering system according to claim 3 , wherein the concept similarity computation unit finds the frequency of appearance of words in the document set by finding the ratio of the number of documents in which the words appear with respect to the number of documents in which the words appear, or the number of documents included in the document set, and by finding the ratio of the number of words appearing with respect to the frequency of the words, which is the number of times that the words appear in the document set, or with respect to the number of documents included in the document set.