In practice, the use of likelihood ratios tends to result in significant improvements in text-analysis performance.
in our problem, LRT computes a contingency table of a pattern p and a word w, derived from the corpus statistics, as given in Table 3, where k 1 (w, p) is the number of documents that w matches pattern p, k 2 (w,p) is the number of documents that w occurs while p does not, k 3 (w, p) is the number of documents that p occurs while w does not, and k 4 (w,p) is the number of documents containing neither p nor w. Based on the statistics shown in Table 3, the likelihood ratio tests (LRT) model captures the statistical association between a pattern p and a word w by employing the following formula: where: the utility of a pattern can be measured as follows: where W is the current word set used in the algorithm (see Algorithm 1).