12. The recommendation system as claimed in claim 8 , wherein the recommendation module is configured to search a k th frequent entity from the k th entity recorded by each of the k th user data in a cluster, search a j th frequent entity from the entities on the j th hierarchy level according to the k th frequent entity, and recommend the j th frequent entity to one of the users corresponding to the k th user data in the one of the cluster.
12. The recommendation system as claimed in claim 8 , wherein the recommendation module is configured to search a k th frequent entity from the k th entity recorded by each of the k th user data in a cluster, search a j th frequent entity from the entities on the j th hierarchy level according to the k th frequent entity, and recommend the j th frequent entity to one of the users corresponding to the k th user data in the one of the cluster. 13. The recommendation system as claimed in claim 12 , wherein the recommendation module is configured to determine whether the k th frequent entity is one of the entities on the j th hierarchy level, map the k th frequent entity to corresponding entities of the entities on a k−1 th hierarchy level of the ontology hierarchy structure in a case that the k th frequent entity is not one of the entities on the j th hierarchy level, and search, through a frequent pattern mining algorithm, a k−1 th frequent entity from the corresponding entities on the k−1 th hierarchy level mapped by the k th frequent entity.