It gives high weights to the topic which appears frequently in a specific document and rarely appears in other documents.
then the relation between and then taking the logarithm, which is calculated as follows: the tFIDF is calculated as follows: the tFIDF score of the topic k over document  the similarity between S m  and t m  is given by: the similarity between  Based on the Bayesian formula, the probability that a given topic  is assigned to a particular target language document t m  is expressed: the sum of all probabilities that all topics  are assigned to a particular document t m  is a constant  , thus equation 8is converted as follows: (9) According to the total probability formula, the similarity between S m  and t m  is given by:  Braschler et al.