8. A computer-executable method of recommending a favorite channel/program, the method comprising: learning, by a processor, a Bayesian network based on received watching pattern information of a user to thereby calculate a first probability value with respect to all of the channels or programs based on the learning result; calculating, by the processor, an entropy of the calculated first probability value, and extracting, when the entropy is less than or equal to a predetermined threshold, any of the channels or programs that corresponds to the calculated first probability value as a candidate favorite channel or program; performing, by the processor, a fuzzy logic inference operation with respect to the extracted candidate favorite channel or program, and calculating a second probability value with respect to each candidate favorite channel or program based on a result of the fuzzy logic inference operation; and determining, by the processor, a favorite channel or program according to the watching pattern information of the user based on the calculated first probability value and second probability value.
14. The method of claim 8 , wherein the watching pattern information comprises an amount of TV watching time for each day, an amount of TV watching time for each time zone, a total amount of watching time for each channel, and an amount of watching time for each program genre.