4. The method as described in claim 3 , wherein for the at least one key product word and the at least one candidate product word, the vectorizing of the at least one key product word using the click through rate for the category of the key product word to obtain the vector, and the vectorizing of the at least one candidate product word using the click through rate for the category of the at least one candidate product word to obtain the vector comprises: for the at least one key product word and the at least one candidate product word, from a search log, separately analyzing and tabulating the click through rates of respective relevant categories to obtain a list of weightings for a relevant category; converting various values in the list of weightings of the at least one key product word into the vector; and converting various values in the list of weightings of the at least one candidate product words into the vector.
5. The method as described in claim 4 , wherein the computing of the angle values between the vectors corresponding to the at least one key product word and the vectors corresponding to the at least one candidate product word, and the selecting of the candidate product word having the correlation that meets the threshold value based on the angle value comprises: computing a cosine angle value of the vectors; determining whether the cosine angle value is greater than the threshold value; and in the event that the cosine angle value is greater than the threshold value, deleting the candidate product word.