19. A computer-implemented method for scoring documents, comprising: (a) receiving document text for a current document that includes at least two words; (b) calculating a prominence score and a descriptiveness score for each word from the current document and each pair of consecutive words from the current document, wherein: the prominence score for each word is based on a term weight and a non-compound likelihood for each word, the prominence score for each pair of consecutive words is based on a term weight and a bigram probability for each pair of consecutive words, a descriptiveness score for each word is based on a corpus, a descriptiveness score for each pair of consecutive words is based on the corpus; and (c) creating a scoring vector for the current document, wherein the scoring vector is based on the combination of each prominence score and each descriptiveness score.
25. The method of claim 19 , wherein the scoring vector creating step (c) further comprises: (i) normalizing the scoring vector, wherein the normalization converts the scoring vector into unit length; and (ii) multiplying the normalized scoring vector by a quality score, wherein the quality score is based on the term weight of each word.